2. Background
RDBMS is not based on regular programing paradigm
It operates on mathematical concept of sets
Sets are groups that have union or intersection or – or X operations
Most misunderstood concept – sets are ordered?
No sets do not guarntee order – very important to know in terms of
RDBMS
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3. Strategic Imperatives
The approach should provide a stable implementation and ease of
management
Provide ability to adapt new design paradigms moving forward
Ease of maintenance for prior code by means of documentation and
code clarity
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4. What’s new in SQL Server 2012
Editions & licensing
Three versions – Standard, Business Intelligence and Enterprise
xVelocity – is Microsoft SQL Server's family of memory-optimized and
in-memory technologies. These are next-generation technologies built
for extreme speed on modern hardware systems with large memories
and many cores
xVelocity In-Memory Analytics Engine (used in PowerPivot and
Analysis Services)
xVelocity Memory-Optimized Columnstore Index (used in the SQL
Server database).
Self Bi – PowerView
Data compression – high performance
Data Quality - Maintain the quality of data and ensure that the data is
suited for business usage
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5. xVelocity – ColumnStore
Column store - In a column store, values from a single column (from multiple
rows) are stored contiguously, potentially in a compressed form
Relational database management systems traditionally store data in row-wise
fashion. The values comprising one row are stored contiguously on a page.
We sometimes refer to data stored in row-wise fashion as a row store
Columnstore index – In SQL Server, a columnstore index is data stored in
column-wise fashion that can be used to answer a query just like data in any
other type of index
A columnstore index appears as an index on a table when examining
catalog views or the Object Explorer in Management Studio
The query optimizer considers the columnstore index as a data source for
accessing data just like it considers other indexes when creating a query
plan
More information:
http://social.technet.microsoft.com/wiki/contents/articles/3540.sql-servercolumnstore-index-faq-en-us.aspx
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6. Power View
Power View is a feature of SQL Server 2012 Reporting Services that is an
interactive data exploration, visualization, and presentation experience
Provides intuitive ad-hoc reporting for business users such as data analysts,
business decision makers, and information workers
Users can easily create and interact with views of data from data models
based on PowerPivot workbooks published in a PowerPivot Gallery, or tabular
models deployed to SQL Server 2012 Analysis Services (SSAS) instances
Power View is a browser-based Silverlight application launched from
SharePoint Server 2010 that enables users to present and share insights with
others in their organization through interactive presentations
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7. Data Compression
DBA can compress tables and indexes to conserve storage space at a slight
CPU cost. One of the main design goals of data compression was to shrink
data warehouse fact tables
SQL Server provides two methods, Page and Row compression, to reduce data
storage on disk and speed I/O performance by reducing the amount of I/O
required for transaction processing. Page and row compression work in
different, yet complementary
Page compression uses an algorithm called “deduplication.” When
deduplicating, as the name implies, SQL Server looks for duplicate values that
appear again and again within the data page
Using page compression, SQL Server can remove such duplicate values within
a data page by replacing each duplicate value with a tiny pointer to a single
appearance of the full value
By comparison, row compression does not actually use a compression
algorithm per se. Instead, when row compression is enabled, SQL Server
simply removes any extra, unused bytes in a fixed data type column, such as a
CHAR(50) column
Page and row compression are not compatible, but by enabling page
compression SQL Server automatically includes row compression
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8. Data Quality Service
Aggregating data from different sources that use different data standards can
result in inconsistent data, as can applying an arbitrary rule or overwriting
historical data. Incorrect data affects the ability of a business to perform
Aggregating data from different sources that use different data standards can
result in inconsistent data, as can applying an arbitrary rule or overwriting
historical data. Incorrect data affects the ability of a business to perform
Features include
Data Cleansing – modification of incorrect or incomplete data
Matching – identification of semantic duplicates
Reference Data Services – verification of quality of data using
reference data provider
Profiling – analysis of a data source to provide insight into the quality of
the data
Monitoring – tracking and determination of the state of data quality
activities
Knowledge Base – Data Quality Services is a knowledge-driven
solution that analyzes data based upon knowledge that you build with
DQS.
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9. Layered Coding Approach
Standardized way for coding
Code level comments
Layered coding – database, business and user interface
Standardized approach on both application and database level
Primary focus of this presentation is at database designing and coding
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10. Resource Utilization
Non-scalable code
Only so many people can access at
the same time
This is caused by
Inefficient use of resources
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Resource locking
Unnecessary use of locks or
transactions that were never
committed or rolled back
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11. Unstructured Data – Paradigm Shift
Non-scalable code
Not only reduces performance
Increases maintenance
Requires more space
Disk space
Disk defragmentation
Requires continuous log file
management, sizing and maintenance
Increased maintenance cost for the
database
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12. Basic Design – that we forget
Defining a table
Key points
Identity columns
Define primary key (if not easily defined then use identity
columns)
Define indices
Huge performance difference using index and primary key
Also helps in joining other tables
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13. Truncate or Delete
Truncate vs. Delete
Using truncate is better than
delete
Why?
What do you think is better for import
tables?
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14. Looping in SQL
Cursors
Necessary evil
Resource hog – disk, network bandwidth (for result transmission
line by line)
Use read only cursor, if there is no update with fast forward option
and auto fetch to get some performance gain
http://technet.microsoft.com/enus/library/aa172573(SQL.80).aspx
Avoid cursors as much as possible
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15. Transactions
Using Transactions
Helpful in recovering from a problem / unexpected situation
Transactions should start as late as possible in the procedure
and end as early as possible to reduce the locking time
Make sure transactions are always rolled back or committed
Handle error using @@error and roll back transactions in
such a case
Use “with Mark” option to add the name to the transaction log
that can be used as a restore point if needed
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http://msdn.microsoft.com/en-us/library/ms188929.aspx
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16. Locks & Deadlocks
Deadlocks and using no locks
Deadlock occurs when two users have
lock on separate objects and each user
is trying to lock other user’s resource
These are automatically detected
and resolved by SQL with one of the
transactions rolled back with an
error code of 1205
Using no locks may be helpful
No locks does not lock a record for read
or write
Advantage?
Pit fall?
Read isolation transaction better
than no lock
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17. Temporary Tables
Temp tables
Using # tables vs. @tables
# tables – pros and cons?
@tables – pros and cons?
Which one should be used for a
stored procedure that is called
very frequently
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18. User Defined Functions
Using User Defined Functions (UDF)
UDF are useful for calculations or results based on some input
UDF are slower than built-in functions
What will happen if we use a UDF in a
Select statement?
Join condition?
Where clause?
Any of the above in a while loop or cursor?
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19. Capturing Error
Using @@error (also trapping errors at application level to close sql
connection and roll back transactions)
Checking @@error variable after and insert and / or update can help
us determining if we need to roll back or commit a transaction
Using Try-catch construct
BEGIN TRY
-- Generate divide-by-zero error.
SELECT 1/0;
END TRY
BEGIN CATCH
-- Execute error retrieval routine.
EXECUTE usp_GetErrorInfo;
END CATCH;
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20. Joins vs. exists or in and not exists or not in
Using left joins with null conditions instead of not exist
Example below
Select z.first_name+' '+z.last_name AS [name],
z.[user_id]
From users z
inner join usergroup zug ON z.[userid] = zug.[userid]
and (z.first_name +z.last_name is not null)
and z.[user_id] NOT IN (SELECT [user_id] FROM Superuser)
inner join groups zg ON zug.group_id = zg.group_id
Where zg.[name]='ADMINISTRATOR'
Order by [name]
We could probably replace the not in with a left join on a = null
Joins are faster than “in” and “not in” and use index
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21. Low hanging fruits
Should Select * be used more frequently?
Scope_Identity vs. select max?
Utilize query analyzer / management studio to view query plan
Analyze for optimization and potential scalability problems
Analyze any potential bottleneck / blocking, use sql trace
Avoid dynamic queries
Use joins potentially on primary key and / or indexed columns
Do not use SP_ in the name of a stored procedure
First reference is checked in master database
Using count(*) vs. Count(Primary key) column
Need to have an ID index
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22. Sub-Queries
Sub-Queries
Avoid sub-queries if possible, they can be a resource hog
ClaimBatch_listDetailXml:
(((@searchClaimType = 'ALL'AND @userId IN( SELECT UserId
FROM NSFClaimTrack nct WHERE nct.UserId = @userId
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23. Conclusion
These are guidelines that will help in
Building a robust product
Standardized way for all programmer
Ease of understanding of code
Clear logic understanding
Easy maintenance
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