SQL Server - Bài 3

SQL Server - Bài

Overview of Transact-SQL

 Based on AINSI SQL 92 standard

 Composing of three categories

 Data Manipulation Language (DML)

 Data Definition Language (DDL)

 Having some Microsoft specific extensions

 Beyond relational data

 net framework integration

Select Data

from the exit table is:

select <the items >

from <name of table>

where <conditions>

Select Data

 You can change the name of the items in the table:

Select Data

 You can insert some items as following:

Select

 Example a function ‘count’ to count the columns of the table:

Select Data

 You can use some functions or some operations in the Select Statement:

Select Data

The Time functions

DATEPART(YY,g etdate())

- DATEDIFF(X,Y,Z )

- DAY(),MONTH(), YEAR()

Select Data

Maths String Time

Oder by Compute For

Into

Having

With

Except , Intersect

Union

Option

Select-With statement

 Specifies a temporary named result set, known as a common table expression (CTE)

Select-Order by

- You can arrange the result follow the first letter by using the order by statement:

Select – multiple tables

 Inner join:

Select-multiple tables

- When you select from more than 1 table, you can use the join…on statement or you can use the cross join statement With the cross join statement, you don’t have to have to

relative condition between the tables and the result is all the Objects:

Select-multiple tables

Select-multiple tables

more tables:

Select-Group by

 Specifies the groups into which output rows are to be placed If aggregate functions are included in the SELECT clause <select list>, GROUP BY calculates a summary value for each group

 Specifies a search condition for a group or an aggregate

 HAVING is typically used in a GROUP BY clause When GROUP BY is not used, HAVING behaves like a WHERE clause

Microsoft

 INTERSECT returns any distinct values that are returned by both the query

on the left and right sides of the INTERSECT operand.

Select-except

 EXCEPT returns any distinct values from the left query that are not also found on the right query

Select-Compute by

 Generates totals that appear as additional summary columns at the end of the result set When used with BY, the COMPUTE clause generates control-breaks and subtotals in the result set You can specify COMPUTE BY and COMPUTE in the same query

Select-Compute by

Select-For clause

 FOR clause is used to specify either the BROWSE or the XML option BROWSE and XML are unrelated options

Select-For clause

Insert

 The simple syntax for Insert statement is:

INSERT INTO<table(x,y,…)>

VALUES(a,b,…)

Insert

- You can insert some values into the table, and you have to insert all the value not null, and the primary key:

Insert

Insert

 If you don’t insert all the column not null, the process will terminate

- You can create a new table and insert the values into that table

Insert

- Inserting data into a unique identifier column by using NEWID()

Insert

- Inserting data into a table through a view

Insert

- Using DELETE on the current row of a cursor

Delete

- Using DELETE based on a subquery and using the SQL extension

- Using DELETE with the TOP clause

Delete

 Using DELETE with the OUTPUT clause

Update

- Using UPDATE with the FROM Clause

- Using the UPDATE statement with information from another table

Update

- Before :

 After

Fulltext Search

 Full-Text Search Architecture

 Administering Full-Text Search

 Querying SQL Server Using Full-Text Search

Overview

Overview

 The architecture consists of the following processes:

 Microsoft Full-Text Engine for SQL Server process (Msftesql.exe)

 Microsoft Full-Text Engine Filter Daemon process (Msftefd.exe)

Full-Text Search Terminology

Administering Full-Text Search

The system stored procedures that are used to implement and query full-text indexes.

DENY permission [ , n ] ON FULLTEXT CATALOG :: full-text_catalog_name TO

database_principal [ , n ] [ CASCADE ] [ AS denying_principal ]

Administering Full-Text Search

Full-text administration can be separated into three main tasks:

 Creating/altering/dropping full-text catalogs

 Creating/altering/dropping full-text indexes

 Scheduling and maintaining index population

Administering Full-Text Search

Full-text indexes Regular SQL Server indexes

Stored in the file system, but

administered through the database.

Stored under the control of the database

in which they are defined.

Only one full-text index allowed per

table. Several regular indexes allowed per table.

Addition of data to full-text indexes,

called population, can be requested

through either a schedule or a specific

request, or can occur automatically with

the addition of new data.

Updated automatically when the data upon which they are based is inserted, updated, or deleted.

Grouped within the same database into

one or more full-text catalogs. Not grouped.

Guidelines in administering full-text indexes

 Like regular SQL Server indexes, full-text indexes can be automatically updated as data is modified in the associated tables Alternatively, you can repopulate full-text indexes manually

at appropriate intervals, but this can be time-consuming and resource-intensive Therefore, index updating is usually performed as an asynchronous process that runs in the background during periods of low database activity.

 Tables with the same update characteristics (such as small number of changes versus large number of changes, or tables that change frequently during a particular time of day) should be grouped together and assigned to the same full-text catalog By setting up full-text catalog population schedules in this way, full-text indexes stay synchronous with the tables without adversely affecting the resource usage of the database server during periods of high database activity.

 It is important to plan the placement of full-text indexes for tables in full-text catalogs When you assign a table to a full-text catalog, consider the following guidelines:

Guidelines in administering full-text indexes (2)

 Always select the smallest unique index available for your full-text unique key (A 4-byte, integer-based index is optimal.) This reduces the resources required by Microsoft Search service in the file system significantly If the primary key is large (over 100 bytes),

consider choosing another unique index in the table (or creating another unique index) as the full-text unique key Otherwise, if the full-text unique key size exceeds the maximum size allowed (900 bytes), full-text population will not be able to proceed.

 If you are indexing a table that has millions of rows, assign the table to its own full-text catalog.

 Consider the amount of change occurring in the tables being full-text indexed, as well as the number of table rows If the total number of rows being changed, together with the numbers of rows in the table present during the last full-text population, represents

millions of rows, assign the table to its own full-text catalog.

Guidelines in administering full-text indexes (3)

 After the word breaker-routine has a list of valid words for a row within a column, the full-text engine calculates tokens to represent the words A token is simply a

compressed form of the original word that saves space and ensures that full-text

indexes can be created in as compact a form as possible.

 The full text-text functionality then builds all tokens in a column into inverted, stacked, compressed structure within a file that is used for search operations This unique structure allows ranking and scoring algorithms to efficiently satisfy possible queries.

Querying SQL Server Using Full-Text Search

Full-Text query keywords

 FREETEXT

 FREETEXTTABLE

 CONTAINS

 CONTAINSTABLE

Querying SQL Server Using Full-Text Search

FREETEXT

FREETEXT ( { column_name | (column_list) | * } , 'freetext_string' [ ,

LANGUAGE language_term ] )

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE [Description] LIKE N'%bike%';

SELECT ProductDescriptionID, Description FROM Production.ProductionDescription WHERE FREETEXT(Description , N’bike’); Must be UNICODE Otherwise prevents a query optimizer from parameter sniffing

Querying SQL Server Using Full-Text Search

Querying SQL Server Using Full-Text Search

FREETEXTTABLE

FREETEXTTABLE (table , { column_name | (column_list) | * } , 'freetext_string'

[ ,LANGUAGE language_term ] [ ,top_n_by_rank ] )

The FREETEXTTABLE version of the previous FREETEXT query would look like this:

SELECT PD.ProductDescriptionID, PD.Description, KEYTBL.[KEY], KEYTBL.RANK FROM Production.ProductDescription AS PD

INNER JOIN FREETEXTTABLE()Production.ProductDescription, Description, N’bike’)

AS KEYTBL ON PD.ProductDescriptionID = KEYTBL.[KEY]

Querying SQL Server Using Full-Text Search

CONTAINS

CONTAINS ( { column_name | (column_list) | * } , '< contains_search_condition

>' [ , LANGUAGE language_term ] ) < contains_search_condition > ::= { <

simple_term > | < prefix_term > | < generation_term > | < proximity_term > | <

weighted_term > } | { ( < contains_search_condition > ) [ { < AND > | < AND NOT

> | < OR > } ] < contains_search_condition > [ n ] } < simple_term > ::= word |

" phrase " < prefix term > ::= { "word * " | "phrase *" } < generation_term > ::=

FORMSOF ( { INFLECTIONAL | THESAURUS } , < simple_term > [ , n ] ) <

proximity_term > ::= { < simple_term > | < prefix_term > } { { NEAR | ~ }

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N'bike');

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N'''bike*'''):

Querying SQL Server Using Full-Text Search

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N' FORMSOF (INFLECTIONAL, bike) ');

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N' FORMSOF (THESAURUS, bike) ');

Word proximity is a common way of searching documents for multiple keywords or phrases This type of query uses the NEAR(~) keyword The closer words are to each other, the better the match for these types of queries The proximity is used as a part of RANK calculation for rows matching the search criteria This keyword is rarely used with the CONTAINS predicate because the rank of matched results cannot be evaluated directly.

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N'mountain NEAR bike');

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, N'mountain ~ bike');

SELECT ProductDescriptionID, Description FROM Production.ProductDescription

WHERE CONTAINS(Description, 'ISABOUT (mountain weight(.8), bike weight (.2) )');

Querying SQL Server Using Full-Text Search

The CONTAINSTABLE function has the same capabilities as the CONTAINS function

However, like the FREETEXTABLE function, it returns a rowset that contains a RANK and

a KEY column that can be used to return the best matches to a search.

CONTAINSTABLE ( table , { column_name | (column_list ) | * } , ' < contains_search_condition

> ' [ , LANGUAGE language_term] [ ,top_n_by_rank ] ) < contains_search_condition > ::=

{ < simple_term > | < prefix_term > | < generation_term > | < proximity_term >

| < weighted_term > } | { ( < contains_search_condition > ) { { AND | & } | { AND

NOT | &! } | { OR | | } } < contains_search_condition > [ n ] } < simple_term > ::=

word | " phrase " < prefix term > ::= { "word * " | "phrase *" } < generation_term > ::= FORMSOF ( { INFLECTIONAL | THESAURUS } , < simple_term > [ , n ] ) <

proximity_term > ::= { < simple_term > | < prefix_term > } { { NEAR | ~ } { <

simple_term > | < prefix_term > } } [ n ] < weighted_term > ::= ISABOUT ( { { <

simple_term > | < prefix_term > | < generation_term > | < proximity_term > }

[ WEIGHT ( weight_value ) ] } [ , n ] )

Querying SQL Server Using Full-Text Search

 Used correctly, will produce more specific, relevant results

 Better performance – LIKE queries are designed for small amounts of text data, full-text search scales to huge documents

 Provides ranking of results

 Search through the content in a text-intensive, database driven website, e.g a knowledge base

 Search the contents of documents stored in BLOB fields

 Perform advanced searches

 e.g with exact phrases - "to be or not to be" (however needs care!)

 e.g Boolean operators - AND, OR, NOT, NEAR

Writing FTS terms

 The power of FTS is in the expression which is passed

to the CONTAINS or CONTAINSTABLE function

 Several different types of terms:

Simple terms

 matches local, locally, locality

 CONTAINS(Column, ' "local wine*" ')

 matches "local winery", "locally wined"

 Supposed to match synonyms of search terms – but the thesaurus seems to be very limited

 Does not match plurals

 Not particularly useful

Proximity terms

 Syntax

CONTAINS(Column, 'local NEAR winery')

CONTAINS(Column, ' "local" NEAR "winery" ')

 Matches words which are NEAR each other

 Terms on either side of NEAR must be either simple or proximity terms

Weighted terms

 Each word can be given a rank

 Can be combined with simple, prefix, generation and proximity terms

performance weight(.8), comfortable weight(.4) )')

FORMSOF(INFLECTIONAL, "performance") weight (.8), FORMSOF(INFLECTIONAL, "comfortable") weight (.4)

Microsoft