Benefits of Normalization

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Normalization produces smaller tables with smaller rows:
• More rows per page (less logical I/O)
• More rows per I/O (more efficient)
• More rows fit in cache (less physical I/O)
• Searching, sorting, and creating indexes is faster, since tables are
narrower, and more rows fit on a data page.
• Index searching is often faster, since indexes tend to be narrower and
shorter.
• More tables allow better use of segments to control physical
placement of data.
• You usually have fewer indexes per table, so data modification
commands are faster.
• You usually have more tables. You can have more clustered indexes (one per table), so you get more
flexibility in tuning queries.
• Fewer null values and less redundant data, making your database
more compact.
• Triggers execute more quickly if you are not maintaining redundant
data.

Happy,Healthy & Successful New Year 2012

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Wishing You Happy , Healthy & Successful New Year 2012!   Happy Learning Sybase!

 

 

 

 

 

 

 

ASE database for SAP ERP

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Hello all,

These are copilataion for Sybase ASE on SAP from the Rob’s Blog :

Read Full Story : http://blogs.sybase.com/database/2011/12/so-what-does-an-ase-database-look-like-in-sap-erp/

  • SAP has released Business Suite on ASE version 15.7.
  • All SAP application data resides in a single ASE database. There is another small database for use by SAP tools.
  • The ASE database uses a 16KB page size.
  • For ERP only (i.e. not counting CRM and the other Business Suite modules), the database contains about 80,000 tables and 170,000 indexes. This is because SAP ERP has many features and functions, all with their own set of tables. SAP customers typically run only a subset of all those functions so in practice a large part of those 80,000 tables will always remain empty.
  • All SAP tables use datarowslocking (there is an interesting historical dimension.
  • All tables names are in uppercase; some table names contain special characters, like the slash character in “/BCV/C_QATTR” (I don’t have a clue what that name means, BTW)
  • Apart from the tables, there are also about 10,000 views. No stored procedures or triggers are used.
  • SAP makes heavy use of dynamic SQL (also known as “prepared statements”).
  • Many tables have a text or image column.
  • All tables are owned by one database user (and that’s not the dbouser).
  • The ASE database is accessed through ODBC.
  • SAP makes frequent use of the built-in ASE Job Scheduler (originally added in ASE 12.5.1).
  • The ASE server uses Unicode with the utf8 character set.

Guidelines for improving I/O performance

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The major guidelines for improving I/O performance in Adaptive Server are as follows:

• Spreading data across disks to avoid I/O contention.

• Isolating server-wide I/O from database I/O.

• Separating data storage and log storage for frequently updated databases.

• Keeping random disk I/O away from sequential disk I/O.

• Mirroring devices on separate physical disks.

• Partitioning tables to match the number of physical devices in a segment.

Logical or Database Devices and Physical Devices

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Distinctions between logical or database devices and physical devices:
———————————————————————-
• The physical disk or physical device is the actual hardware that stores the data.

• A database device or logical device is a piece of a physical disk that has been initialized (with the disk init command) for use by Adaptive Server. A database device can be an operating system file, an entire disk, or a disk partition.

• A segment is a named collection of database devices used by a database. The database devices that make up a segment can be located on separate physical devices.

• A partition is block of storage for a table. Partitioning a table splits it so that multiple tasks can access it simultaneously. When partitioned tables are placed on segments with a matching number of devices, each partition starts on a separate database device.

sp_helpdevice –> To get information about devices
sp_helpsegment –> To get information about segments
sp_helpartition –> To get information about partitions.

Sybase IQ 15 Best Practices Guide

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Full Arcticle : http://www.sybase.com/files/White_Papers/SybaseIQ15_best_practices_wp20110718.pdf

 


 

What’s in YOUR Architecture?

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What’s in your architecture?

Probably not enough if you’re using just data modeling to integrate all the components of your enterprise, especially your information. To lay the
foundation of this paper, let’s start from the same level of understanding: the need for a common approach to managing all the aspects of information to
enable rapid business performance in the 21st century economy.

Competition in the marketplace is always fierce. To stay abreast, organizations must constantly analyze their customer needs and expectations, enhance
or innovate their business processes, and deliver products and services that create exceptional customer value. Organizations also need to be customercentric to forge long-term relationships with clients and consumers. Only organizations that are agile enough to respond to volatile market conditions
with innovation, expedited time-to-market processes, and reduced costs can differentiate themselves from the competition. Such agility occurs when a
company’s IT operations are closely aligned with its business operations. IT needs to understand business to implement technologies and applications that
support the current and future business goals.

Read Full Article @ http://www.sybase.com/files/White_Papers/Sybase_Whats_in_Your_Architecture_WP.pdf

K21– ASE’S KERNEL DESIGN FOR THE 21ST CENTURY – ASE 15.7’s THREADED KERNEL K21

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Basic Difference :

Process Kernel:

Pre-15.7 kernel (except Windows)
Each engine is a separate process

Retained in 15.7 for risk mitigation

Threaded Kernel:

Default kernel for 15.7

Each engine is a thread of a single process

Additional threads for handling I/O, etc.

ASE on Windows has always been thread based

http://www.sybase.com/files/Product_Overviews/ASE-15.7-New-Threaded-Kernel.pdf

http://blogs.sybase.com/tradingandrisk/2011/11/highly-consistent-response-times-with-new-threaded-kernel-in-ase-15-7/

How to run sybase query in different databases in one run

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I would suggest to run SQL via shell script as below.

database.txt

————

database1

database2

database3

 

query.txt

———

select col1, col2 from table

go

write shell script

multiple_database_query.sh

————————–

while read LINE

do

database=$LINE

isql -S “” -D “${database}” -i “query.txt”

done < database.txt

 

Database load error

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Sometime “database is in use” error encounters while loading the database, this could be due to in-memory db tables might still active for the named database. So use the dbcc commands to clear those and reload the database.

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