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Factory pattern Vs Abstract Factory pattern
Factory: A factory that creates objects that derive from a particular base class.
Abstract factory: A factory that creates other factories, and these factories in turn create objects derived from base classes. You do this because you often don’t just want to create a single object (as with Factory method) – rather, you want to create a collection of related objects.
Real Life Example. (Easy to remember)
Factory
Imagine you are constructing a house and you approach a carpenter for a door. You give the measurement for the door and your requirements, and he will construct a door for you. In this case, the carpenter is a factory of doors. Your specifications are inputs for the factory, and the door is the output or product from the factory.
Abstract Factory
Now, consider the same example of the door. You can go to a carpenter, or you can go to a plastic door shop or a PVC shop. All of them are door factories. Based on the situation, you decide what kind of factory you need to approach. This is like an Abstract Factory.
The Object Class
The Object class is a special type that is the base class for all other classes and types, including the value types. It defines a set of methods that are therefore inherited by every other type that is defined within the .NET framework class library.
What is the Object Class?
The Object class, held in the System namespace, is the base class for all classes and data types, including the value types. It is the class at the root of the .NET framework class library’s entire type hierarchy.
System.Object defines several public and protected methodsthat, due to inheritance, are automatically made available to all .NET classes, structures and types, including any classes or structures that you create yourself. If you create a class with no base class specified, it will implicitly derive functionality from Object.
Often developers overlookthe Object class. However, its importance is significant and the complexities if its members should be understood.
object = Object
The C# programming language declares a data type named “object”. This type is simply an alias for System.Object and so the two terms are interchangeable; they differ in capitalisation but not functionality.
Object methods
The Object class defines seven base methods. Of these, five are public methods that are available to be called by external objects. The remaining two methods are protected. These are only accessible internally and to derived classes. Each of the methods is described in the following sections.
Public Methods
Equals Method
The Equals method is used to compare two objects to determine if they are equal. The comparison of the objects depends upon their types. For the value types, a bit-by-bit comparison of the two values is made. If they are a perfect match, the method returns true. If not, the method returns false.
When comparing reference types, the values of the two references are compared. Only when both references are pointing to the same object does the method return true. If the properties of two objects are a perfect match but the references are different, the method returns false.
The Equals method can be overridden in a subclass. This permits the behaviour to be changed so that it is more appropriate. For example, in the case of the string data type, Equals is overridden so that a comparison of two strings can be made as though they were value types. Even when the two strings contain different references, if the underlying characters match, the method returns true.
string s1 = "Hello";string s2 = "Hello";bool result = s1.Equals(s2); // result = true |
The Equals method is available in two forms. The instance version is shown in the above example. In this case, the method requires a single parameter containing the item to be compared to the invoking object. A static version of the method is also available. This requires two parameters, one for each of the items to be compared. The above example could therefore be rewritten as:
string s1 = "Hello";string s2 = "Hello";bool result = string.Equals(s1, s2); // result = true |
When overriding the behaviour of the Equals method, there are several rules that must be followed to ensure correct operation. These are:
- A call to x.Equals(x), where “x” is a variable of the class in question, must return true. The only exception to this rule is in the comparison of floating point data, where you may decide that a variable containing NaN (not a number) is not equivalent to itself. NB: Interestingly, the floating point types in the .NET framework return true when comparing NaN to NaN using the Equals method, but false when using the == operator. The == operator matches theIEC 60559:1989 specification whilst the Equals method does not.
- A call to x.Equals(y) must return the same result as a call to y.Equals(x).
- The expression “x.Equals(y) && y.Equals(z)” must only return true if x.Equals(z) returns true.
- If x and y are not modified, successive calls to x.Equals(y) must return consistent results.
- A call to x.Equals(null) must return false.
- If the == operator is overloaded, the Equals method must be overridden to provide matching functionality, except in the case of floating point value types.
- If Equals is overridden, the GetHashCode method must also be overridden for compatibility. Otherwise,Hashtables may function incorrectly.
- If a class implements the IComparable interface, the Equals method should be overridden.
- The Equals method must not throw exceptions.
GetHashCode Method
The GetHashCode method provides an algorithm to generate a hash code for an object. Hash codes are used when creatinghash tables to permit objects to be found quickly in large sets of data. The GetHashCode method is used by the Hashtable collection class for this purpose.
The GetHashCode method returns an integer containing the hash code for an object. The value is not unique and should not be used as an identifier or for any purposes other than when using a hashing function. This is particularly relevant when using multiple versions of the .NET framework as the hashing algorithms for classes vary between versions, leading to different results for identical objects.
You can see examples of the return values by executing the following code. The results shown are generated using version 3.5 of the .NET framework and may differ from those you see.
int i = 10;float f = 10;string s = "Hello";int result;result = i.GetHashCode(); // result = 10result = f.GetHashCode(); // result = 1092616192result = s.GetHashCode(); // result = -694847 |
The GetHashCode method can be overridden. When doing so, the following guidelines should be followed:
- If GetHashCode is overridden, the Equals method must also be overridden for compatibility. Otherwise, Hashtables may function incorrectly.
- The value returned from the hashing algorithm must be appropriate for value types. Two values that would be considered equal when using the Equals method must return the same hash code.
- The hash codes generated by the algorithm should be well distributed amongst the available range of integer return values. If the algorithm produces many duplicates or similar values, the performance of Hashtables will be impacted.
- The hashing algorithm should be as fast and efficient as possible to avoid performance issues with Hashtables.
- The GetHashCode method must not throw exceptions.
GetType Method
The GetType method simply returns the type of the object that invokes it. This is useful when using polymorphismtechniques as the type of the underlying object can be identified, even if held in a variable declared as another type. For example, if “Dog” is a subclass of “Animal” and a Dog object is being held in an Animal variable, the type returned will still be Dog. The method is also used for reflection.
The type is returned in a System.Type object. A detailed description of the System.Type class is beyond the scope of this article. For demonstration purposes we will simply output a string representation of the type to the console.
string s = "Hello";Console.WriteLine(s.GetType()); // Outputs "System.String"object o = s;Console.WriteLine(o.GetType()); // Outputs "System.String" |
ReferenceEquals Method
The ReferenceEquals method is a static member of the Object class. It is used with reference types to determine if two instances of a class contain the same reference. If the references are the same, the method returns true. If the references are different, the method returns false, even if the values of the two instances match. If the two items to be compared are both null, the resultant value is true. If they are two value types, the result is always false.
The method is called with two parameters, each holding one of the references to be compared.
object o1 = new object();object o2 = new object();object o3 = o1;bool result;result = object.ReferenceEquals(o1, o2); // result = falseresult = object.ReferenceEquals(o1, o3); // result = trueint i1 = 1;int i2 = 1;result = object.ReferenceEquals(i1, i2); // result = false |
ToString Method
The ToString method is probably the most well-known and used member of the Object class. This method returns a human-readable, string representation of the current object. The default behaviour is to return the fully qualified name of the object’s type. However, this can be overridden to provide a more useful value, as in the case of thenumeric types where the ToString method is overridden and overloaded to allow the creation of formatted numeric strings.
The base version of ToString provided by the Object class accepts no parameters.
object o = new object();Console.WriteLine(o.ToString()); // Outputs "System.Object" |
Protected Methods
Finalize Method
The Finalize method is the first protected method of the Object class that we will consider. This method permits objects to clean up any resources and perform any other activities that are required before an object that is no longer required is reclaimed by the garbage collector. Finalizers in C# are declared as destructors.
The Finalize method cannot be overridden and may not be called during the normal execution of a program. The method is called automatically after an object is no longer accessible, due to all references to it being removed or going out of scope. However, there is no guarantee of the exact execution time of the Finalize method and certainly no assumption that it will run immediately should be made. It is also possible that the finalizer will not run at all if another Finalize method is blocked indefinitely or if the program terminates abnormally.
If two objects become inaccessible at the same time, there is no guarantee of the order in which their finalizers will be called. This is still the case when one of the objects refers to the other.
Classes must implement a destructor when they use unmanaged resources such as database connections or file handles. These resources cannot be reclaimed by the garbage collector and will otherwise not be correctly released. However, in these cases, the class should also implement the IDisposable interface.
MemberwiseClone Method
The MemberwiseClone method is used to create a shallow copy of an object. A shallow copy of an object contains the same values and references as the original. For value type members, this is a bitwise copy of the member data. For reference type members the reference only is copied, meaning that the copy and the original are references to the same object. The method is called with no parameters and returns the cloned object as a System.Object that may be cast to the correct type as required.
Association, Aggregation, Composition
en we have only one relationship between objects, that is called Association. Aggregation and Composition both are specialized form of Association. Composition is again specialize form of Aggregation.
Association is a relationship where all object have their own lifecycle and there is no owner. Let’s take an example of Teacher and Student. Multiple students can associate with single teacher and single student can associate with multiple teachers but there is no ownership between the objects and both have their own lifecycle. Both can create and delete independently.
Aggregation is a specialize form of Association where all object have their own lifecycle but there is ownership and child object can not belongs to another parent object. Let’s take an example of Department and teacher. A single teacher can not belongs to multiple departments, but if we delete the department teacher object will not destroy. We can think about “has-a” relationship.
Composition is again specialize form of Aggregation and we can call this as a “death” relationship. It is a strong type of Aggregation. Child object dose not have their lifecycle and if parent object deletes all child object will also be deleted. Let’s take again an example of relationship between House and rooms. House can contain multiple rooms there is no independent life of room and any room can not belongs to two different house if we delete the house room will automatically delete. Let’s take another example relationship between Questions and options. Single questions can have multiple options and option can not belong to multiple questions. If we delete questions options will automatically delete.
Select Find Nth Highest Salary Record In Sql Server
1st Method :
SELECT TOP 1 [Salary]
FROM
(
SELECT DISTINCT TOP N [Salary]
FROM [dbo].[Employee]
ORDER BY [Salary] DESC
) temp
ORDER BY [Salary]
2nd Method :
SELECT * FROM
(
SELECT DENSE_RANK() OVER(ORDER BY [Salary] DESC)AS RowId, *
FROM [dbo].[Employee]
) AS e1
WHERE e1.RowId = N
http://csharpdotnetfreak.blogspot.com/2011/09/select-nth-highest-record-sql-server.html
Database Normalization
Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency.
Redundant data wastes disk space and creates maintenance problems. If data that exists in more than one place must be changed, the data must be changed in exactly the same way in all locations. A customer address change is much easier to implement if that data is stored only in the Customers table and nowhere else in the database.
What is an “inconsistent dependency”? While it is intuitive for a user to look in the Customers table for the address of a particular customer, it may not make sense to look there for the salary of the employee who calls on that customer. The employee’s salary is related to, or dependent on, the employee and thus should be moved to the Employees table. Inconsistent dependencies can make data difficult to access because the path to find the data may be missing or broken.
There are a few rules for database normalization. Each rule is called a “normal form.” If the first rule is observed, the database is said to be in “first normal form.” If the first three rules are observed, the database is considered to be in “third normal form.” Although other levels of normalization are possible, third normal form is considered the highest level necessary for most applications.
As with many formal rules and specifications, real world scenarios do not always allow for perfect compliance. In general, normalization requires additional tables and some customers find this cumbersome. If you decide to violate one of the first three rules of normalization, make sure that your application anticipates any problems that could occur, such as redundant data and inconsistent dependencies.
The following descriptions include examples.
First Normal Form
- Eliminate repeating groups in individual tables.
- Create a separate table for each set of related data.
- Identify each set of related data with a primary key.
Do not use multiple fields in a single table to store similar data. For example, to track an inventory item that may come from two possible sources, an inventory record may contain fields for Vendor Code 1 and Vendor Code 2.
What happens when you add a third vendor? Adding a field is not the answer; it requires program and table modifications and does not smoothly accommodate a dynamic number of vendors. Instead, place all vendor information in a separate table called Vendors, then link inventory to vendors with an item number key, or vendors to inventory with a vendor code key.
Second Normal Form
- Create separate tables for sets of values that apply to multiple records.
- Relate these tables with a foreign key.
Records should not depend on anything other than a table’s primary key (a compound key, if necessary). For example, consider a customer’s address in an accounting system. The address is needed by the Customers table, but also by the Orders, Shipping, Invoices, Accounts Receivable, and Collections tables. Instead of storing the customer’s address as a separate entry in each of these tables, store it in one place, either in the Customers table or in a separate Addresses table.
Third Normal Form
- Eliminate fields that do not depend on the key.
Values in a record that are not part of that record’s key do not belong in the table. In general, any time the contents of a group of fields may apply to more than a single record in the table, consider placing those fields in a separate table.
For example, in an Employee Recruitment table, a candidate’s university name and address may be included. But you need a complete list of universities for group mailings. If university information is stored in the Candidates table, there is no way to list universities with no current candidates. Create a separate Universities table and link it to the Candidates table with a university code key.
EXCEPTION: Adhering to the third normal form, while theoretically desirable, is not always practical. If you have a Customers table and you want to eliminate all possible interfield dependencies, you must create separate tables for cities, ZIP codes, sales representatives, customer classes, and any other factor that may be duplicated in multiple records. In theory, normalization is worth pursing. However, many small tables may degrade performance or exceed open file and memory capacities.
It may be more feasible to apply third normal form only to data that changes frequently. If some dependent fields remain, design your application to require the user to verify all related fields when any one is changed.
–
Other Normalization Forms
Fourth normal form, also called Boyce Codd Normal Form (BCNF), and fifth normal form do exist, but are rarely considered in practical design. Disregarding these rules may result in less than perfect database design, but should not affect functionality.
Normalizing an Example Table
These steps demonstrate the process of normalizing a fictitious student table.
- Unnormalized table:
Student# Advisor Adv-Room Class1 Class2 Class3 1022 Jones 412 101-07 143-01 159-02 4123 Smith 216 201-01 211-02 214-01 - First Normal Form: No Repeating GroupsTables should have only two dimensions. Since one student has several classes, these classes should be listed in a separate table. Fields Class1, Class2, and Class3 in the above records are indications of design trouble.Spreadsheets often use the third dimension, but tables should not. Another way to look at this problem is with a one-to-many relationship, do not put the one side and the many side in the same table. Instead, create another table in first normal form by eliminating the repeating group (Class#), as shown below:
Student# Advisor Adv-Room Class# 1022 Jones 412 101-07 1022 Jones 412 143-01 1022 Jones 412 159-02 4123 Smith 216 201-01 4123 Smith 216 211-02 4123 Smith 216 214-01 - Second Normal Form: Eliminate Redundant DataNote the multiple Class# values for each Student# value in the above table. Class# is not functionally dependent on Student# (primary key), so this relationship is not in second normal form.The following two tables demonstrate second normal form:Students:
Student# Advisor Adv-Room 1022 Jones 412 4123 Smith 216 Registration:
Student# Class# 1022 101-07 1022 143-01 1022 159-02 4123 201-01 4123 211-02 4123 214-01 - Third Normal Form: Eliminate Data Not Dependent On KeyIn the last example, Adv-Room (the advisor’s office number) is functionally dependent on the Advisor attribute. The solution is to move that attribute from the Students table to the Faculty table, as shown below:Students:
Student# Advisor 1022 Jones 4123 Smith Faculty:
Name Room Dept Jones 412 42 Smith 216 42
Difference between String and StringBuffer/StringBuilder
Well, the most important difference between String and StringBuffer/StringBuilder is that String object is immutable whereas StringBuffer/StringBuilder objects are mutable.
By immutable, we mean that the value stored in the String object cannot be changed. Then the next question that comes to our mind is “If String is immutable then how am I able to change the contents of the object whenever I wish to?” . Well, to be precise it’s not the same String object that reflects the changes you do. Internally a new String object is created to do the changes.
So suppose you declare a String object:
String myString = “Hello”;
Next, you want to append “Guest” to the same String. What do you do?
myString = myString + ” Guest”;
When you print the contents of myString the output will be “Hello Guest”. Although we made use of the same object(myString), internally a new object was created in the process. So, if you were to do some string operation involving an append or trim or some other method call to modify your string object, you would really be creating those many new objects of class String.
Now isn’t that a performance issue?
Yes, it definitely is.
Then how do you make your string operations efficient?
By using StringBuffer or StringBuilder.
How would that help?
Well, since StringBuffer/StringBuilder objects are mutable, we can make changes to the value stored in the object. What this effectively means is that string operations such as append would be more efficient if performed using StringBuffer/StringBuilder objects than String objects.
Finally, whats the difference between StringBuffer and StringBuilder?
StringBuffer and StringBuilder have the same methods with one difference and that’s of synchronization. StringBuffer is synchronized( which means it is thread safe and hence you can use it when you implement threads for your methods) whereas StringBuilder is not synchronized( which implies it isn’t thread safe).
So, if you aren’t going to use threading then use the StringBuilder class as it’ll be more efficient than StringBuffer due to the absence ofsynchronization.
Optimize SQL Queries (Theory an Practice)
This article assumes you already know SQL and want to optimize queries.
The reasons to optimize
Time is money and people don’t like to wait so programs are expected to be fast.
In Internet time and client/server programming, it’s even more true because suddenly a lot of people are waiting for the DB to give them an answer which makes response time even longer.
Even if you use faster servers, this has been proven to be a small factor compared to the speed of the algorithm used. Therefore, the solution lies in optimization.
Theory of optimization
There are many ways to optimize Databases and queries. My method is the following.
Look at the DB Schema and see if it makes sense
Most often, Databases have bad designs and are not normalized. This can greatly affect the speed of your Database. As a general case, learn the 3 Normal Forms and apply them at all times. The normal forms above 3rd Normal Form are often called de-normalization forms but what this really means is that they break some rules to make the Database faster.
What I suggest is to stick to the 3rd normal form except if you are a DBA (which means you know subsequent forms and know what you’re doing). Normalization after the 3rd NF is often done at a later time, not during design.
Only query what you really need
Filter as much as possible
Your Where Clause is the most important part for optimization.
Select only the fields you need
Never use “Select *” — Specify only the fields you need; it will be faster and will use less bandwidth.
Be careful with joins
Joins are expensive in terms of time. Make sure that you use all the keys that relate the two tables together and don’t join to unused tables — always try to join on indexed fields. The join type is important as well (INNER, OUTER,… ).
Optimize queries and stored procedures (Most Run First)
Queries are very fast. Generally, you can retrieve many records in less than a second, even with joins, sorting and calculations. As a rule of thumb, if your query is longer than a second, you can probably optimize it.
Start with the Queries that are most often used as well as the Queries that take the most time to execute.
Add, remove or modify indexes
If your query does Full Table Scans, indexes and proper filtering can solve what is normally a very time-consuming process. All primary keys need indexes because they makes joins faster. This also means that all tables need a primary key. You can also add indexes on fields you often use for filtering in the Where Clauses.
You especially want to use Indexes on Integers, Booleans, and Numbers. On the other hand, you probably don’t want to use indexes on Blobs, VarChars and Long Strings.
Be careful with adding indexes because they need to be maintained by the database. If you do many updates on that field, maintaining indexes might take more time than it saves.
In the Internet world, read-only tables are very common. When a table is read-only, you can add indexes with less negative impact because indexes don’t need to be maintained (or only rarely need maintenance).
Move Queries to Stored Procedures (SP)
Stored Procedures are usually better and faster than queries for the following reasons:
Stored Procedures are compiled (SQL Code is not), making them faster than SQL code.
SPs don’t use as much bandwidth because you can do many queries in one SP. SPs also stay on the server until the final results are returned.
Stored Procedures are run on the server, which is typically faster.
Calculations in code (VB, Java, C++, …) are not as fast as SP in most cases.
It keeps your DB access code separate from your presentation layer, which makes it easier to maintain (3 tiers model).
Remove unneeded Views
Views are a special type of Query — they are not tables. They are logical and not physical so every time you run select * from MyView, you run the query that makes the view and your query on the view.
If you always need the same information, views could be good.
If you have to filter the View, it’s like running a query on a query — it’s slower.
Tune DB settings
You can tune the DB in many ways. Update statistics used by the optimizer, run optimization options, make the DB read-only, etc… That takes a broader knowledge of the DB you work with and is mostly done by the DBA.
Using Query Analysers
In many Databases, there is a tool for running and optimizing queries. SQL Server has a tool called the Query Analyser, which is very useful for optimizing. You can write queries, execute them and, more importantly, see the execution plan. You use the execution to understand what SQL Server does with your query.
Optimization in Practice
Example 1:
I want to retrieve the name and salary of the employees of the R&D department.
Original:
Query : Select * From Employees
In Program : Add a filter on Dept or use command : if Dept = R&D–
Corrected :
Select Name, Salary From Employees Where Dept = R&D–
In the corrected version, the DB filters data because it filters faster than the program.
Also, you only need the Name and Salary, so only ask for that.
The data that travels on the network will be much smaller, and therefore your performances will improve.
Example 2 (Sorting):
Original:
Select Name, Salary
From Employees
Where Dept = ‘R&D’
Order By Salary
Do you need that Order By Clause? Often, people use Order By in development to make sure returned data are ok; remove it if you don’t need it.
If you need to sort the data, do it in the query, not in the program.
Example 3:
Original:
For i = 1 to 2000
Call Query : Select salary From Employees Where EmpID = Parameter(i)
Corrected:
Select salary From Employees Where EmpID >= 1 and EmpID <= 2000
The original Query involves a lot of network bandwidth and will make your whole system slow.
You should do as much as possible in the Query or Stored Procedure. Going back and forth is plain stupid.
Although this example seems simple, there are more complex examples on that theme.
Sometimes, the processing is so great that you think it’s better to do it in the code but it’s probably not.
Sometimes, your Stored Procedure will be better off creating a temporary table, inserting data in it and returning it than going back and forth 10,000 times. You might have a slower query that saves time on a greater number of records or that saves bandwidth.
Example 4 (Weak Joins):
You have two tables Orders and Customers. Customers can have many orders.
Original:
Select O.ItemPrice, C.Name
From Orders O, Customers C
Corrected:
Select O.ItemPrice, C.Name
From Orders O, Customers C
Where O.CustomerID = C.CustomerID
In that case, the join was not there at all or was not there on all keys. That would return so many records that your query might take hours. It’s a common mistake for beginners.
Corrected 2:
Depending on the DB you use, you will need to specify the Join type you want in different ways.
In SQL Server, the query would need to be corrected to:
Select O.ItemPrice, C.Name
From Orders O INNER JOIN Customers C ON O.CustomerID = C.CustomerID
Choose the good join type (INNER, OUTER, LEFT, …).
Note that in SQL Server, Microsoft suggests you use the joins like in the Corrected 2 instead of the joins in the Where Clause because it will be more optimized.
Example 5 (Weak Filters):
This is a more complicated example, but it illustrates filtering at its best.
We have two tables — Products (ProductID, DescID, Price) and Description(DescID, LanguageID, Text). There are 100,000 Products and unfortunately we need them all.
There are 100 languages (LangID = 1 = English). We only want the English descriptions for the products.
We are expecting 100 000 Products (ProductName, Price).
First try:
Select D.Text As ProductName, P.Price
From Products P INNER JOIN Description D On P.DescID = D.DescID
Where D.LangID = 1
That works but it will be really slow because your DB needs to match 100,000 records with 10,000,000 records and then filter that Where LangID = 1.
The solution is to filter On LangID = 1 before joining the tables.
Corrected:
Select D.Text As ProductName, P.Price
From (Select DescID, Text From Description Where D.LangID = 1) D
INNER JOIN Products P On D.DescID = P.DescID
Now, that will be much faster. You should also make that query a Stored Procedure to make it faster.
Example 6 (Views):
Create View v_Employees AS
Select * From Employees
Select * From v_Employees
This is just like running Select * From Employees twice.
You should not use the view in that case.
If you were to always use the data for employees of R&D and would not like to give the rights to everyone on that table because of salaries being confidential, you could use a view like that:
Create View v_R&DEmployees AS
Select Name, Salary From Employees Where Dept = 1
(Dept 1 is R&D).
You would then give the rights to View v_R&DEmployees to some people and would restrict the rights to Employees table to the DBA only.
That would be a possibly good use of views.
Conclusion
I hope this will help you make your queries faster and your databases more optimized. This should make your program look better and can possibly mean money, especially for high load web applications where it means your program can serve more transactions per hour and you often get paid by transaction.
While you can put the above examples to practice in your database of choice, the preceding tips are especially true for major Databases like Oracle or SQL Server.
****************************************************************************************************
SQL Tuning/SQL Optimization Techniques:
1) The sql query becomes faster if you use the actual columns names in SELECT statement instead of than ‘*’.
For Example: Write the query as
SELECT id, first_name, last_name, age, subject FROM student_details;
Instead of:
SELECT * FROM student_details;
2) HAVING clause is used to filter the rows after all the rows are selected. It is just like a filter. Do not use HAVING clause for any other purposes.
For Example: Write the query as
SELECT subject, count(subject)
FROM student_details
WHERE subject != ‘Science’
AND subject != ‘Maths’
GROUP BY subject;
Instead of:
SELECT subject, count(subject)
FROM student_details
GROUP BY subject
HAVING subject!= ‘Vancouver’ AND subject!= ‘Toronto’;
3) Sometimes you may have more than one subqueries in your main query. Try to minimize the number of subquery block in your query.
For Example: Write the query as
SELECT name
FROM employee
WHERE (salary, age ) = (SELECT MAX (salary), MAX (age)
FROM employee_details)
AND dept = ‘Electronics’;
Instead of:
SELECT name
FROM employee
WHERE salary = (SELECT MAX(salary) FROM employee_details)
AND age = (SELECT MAX(age) FROM employee_details)
AND emp_dept = ‘Electronics’;
4) Use operator EXISTS, IN and table joins appropriately in your query.
a) Usually IN has the slowest performance.
b) IN is efficient when most of the filter criteria is in the sub-query.
c) EXISTS is efficient when most of the filter criteria is in the main query.
For Example: Write the query as
Select * from product p
where EXISTS (select * from order_items o
where o.product_id = p.product_id)
Instead of:
Select * from product p
where product_id IN
(select product_id from order_items
5) Use EXISTS instead of DISTINCT when using joins which involves tables having one-to-many relationship.
For Example: Write the query as
SELECT d.dept_id, d.dept
FROM dept d
WHERE EXISTS ( SELECT ‘X’ FROM employee e WHERE e.dept = d.dept);
Instead of:
SELECT DISTINCT d.dept_id, d.dept
FROM dept d,employee e
WHERE e.dept = e.dept;
6) Try to use UNION ALL in place of UNION.
For Example: Write the query as
SELECT id, first_name
FROM student_details_class10
UNION ALL
SELECT id, first_name
FROM sports_team;
Instead of:
SELECT id, first_name, subject
FROM student_details_class10
UNION
SELECT id, first_name
FROM sports_team;
7) Be careful while using conditions in WHERE clause.
For Example: Write the query as
SELECT id, first_name, age FROM student_details WHERE age > 10;
Instead of:
SELECT id, first_name, age FROM student_details WHERE age != 10;
Write the query as
SELECT id, first_name, age
FROM student_details
WHERE first_name LIKE ‘Chan%’;
Instead of:
SELECT id, first_name, age
FROM student_details
WHERE SUBSTR(first_name,1,3) = ‘Cha’;
Write the query as
SELECT id, first_name, age
FROM student_details
WHERE first_name LIKE NVL ( :name, ‘%’);
Instead of:
SELECT id, first_name, age
FROM student_details
WHERE first_name = NVL ( :name, first_name);
Write the query as
SELECT product_id, product_name
FROM product
WHERE unit_price BETWEEN MAX(unit_price) and MIN(unit_price)
Instead of:
SELECT product_id, product_name
FROM product
WHERE unit_price >= MAX(unit_price)
and unit_price <= MIN(unit_price)
Write the query as
SELECT id, name, salary
FROM employee
WHERE dept = ‘Electronics’
AND location = ‘Bangalore’;
Instead of:
SELECT id, name, salary
FROM employee
WHERE dept || location= ‘ElectronicsBangalore’;
Use non-column expression on one side of the query because it will be processed earlier.
Write the query as
SELECT id, name, salary
FROM employee
WHERE salary < 25000;
Instead of:
SELECT id, name, salary
FROM employee
WHERE salary + 10000 < 35000;
Write the query as
SELECT id, first_name, age
FROM student_details
WHERE age > 10;
Instead of:
SELECT id, first_name, age
FROM student_details
WHERE age NOT = 10;
8) Use DECODE to avoid the scanning of same rows or joining the same table repetitively. DECODE can also be made used in place of GROUP BY or ORDER BY clause.
For Example: Write the query as
SELECT id FROM employee
WHERE name LIKE ‘Ramesh%’
and location = ‘Bangalore’;
Instead of:
SELECT DECODE(location,’Bangalore’,id,NULL) id FROM employee
WHERE name LIKE ‘Ramesh%’;
9) To store large binary objects, first place them in the file system and add the file path in the database.
10) To write queries which provide efficient performance follow the general SQL standard rules.
a) Use single case for all SQL verbs
b) Begin all SQL verbs on a new line
c) Separate all words with a single space
d) Right or left aligning verbs within the initial SQL verb
Lock, Monitor, Mutex, Semaphore
Locking
Exclusive locking is used to ensure that only one thread can enter particular sections of code at a time. The two main exclusive locking constructs are lock and Mutex. Of the two, the lock construct is faster and more convenient.Mutex, though, has a niche in that its lock can span applications in different processes on the computer.
Let’s start with the following class:
class ThreadUnsafe
{
static int _val1 = 1, _val2 = 1;
static void Go()
{
if (_val2 != 0) Console.WriteLine (_val1 / _val2);
_val2 = 0;
}
}
This class is not thread-safe: if Go was called by two threads simultaneously, it would be possible to get a division-by-zero error, because _val2 could be set to zero in one thread right as the other thread was in between executing the if statement and Console.WriteLine.
Here’s how lock can fix the problem:
class ThreadSafe
{
static readonly object _locker = new object();
static int _val1, _val2;
static void Go()
{
lock (_locker)
{
if (_val2 != 0) Console.WriteLine (_val1 / _val2);
_val2 = 0;
}
}
}
Only one thread can lock the synchronizing object (in this case, _locker) at a time, and any contending threads areblocked until the lock is released. If more than one thread contends the lock, they are queued on a “ready queue” and granted the lock on a first-come, first-served basis (a caveat is that nuances in the behavior of Windows and the CLR mean that the fairness of the queue can sometimes be violated). Exclusive locks are sometimes said to enforceserialized access to whatever’s protected by the lock, because one thread’s access cannot overlap with that of another. In this case, we’re protecting the logic inside the Go method, as well as the fields _val1 and _val2.
Monitor.Enter and Monitor.Exit
C#’s lock statement is in fact a syntactic shortcut for a call to the methods Monitor.Enter and Monitor.Exit, with atry/finally block. Here’s (a simplified version of) what’s actually happening within the Go method of the preceding example:
Monitor.Enter (_locker);
try
{
if (_val2 != 0) Console.WriteLine (_val1 / _val2);
_val2 = 0;
}
finally { Monitor.Exit (_locker); }
Calling Monitor.Exit without first calling Monitor.Enter on the same object throws an exception.
Mutex
A Mutex is like a C# lock, but it can work across multiple processes. In other words, Mutex can be computer-wideas well as application-wide.
Acquiring and releasing an uncontended Mutex takes a few microseconds — about 50 times slower than a lock.
With a Mutex class, you call the WaitOne method to lock and ReleaseMutex to unlock. Closing or disposing aMutex automatically releases it. Just as with the lock statement, a Mutex can be released only from the same thread that obtained it.
A common use for a cross-process Mutex is to ensure that only one instance of a program can run at a time. Here’s how it’s done:
class OneAtATimePlease
{
static void Main()
{
// Naming a Mutex makes it available computer-wide. Use a name that's
// unique to your company and application (e.g., include your URL).
using (var mutex = new Mutex (false, "oreilly.com OneAtATimeDemo"))
{
// Wait a few seconds if contended, in case another instance
// of the program is still in the process of shutting down.
if (!mutex.WaitOne (TimeSpan.FromSeconds (3), false))
{
Console.WriteLine ("Another app instance is running. Bye!");
return;
}
RunProgram();
}
}
static void RunProgram()
{
Console.WriteLine ("Running. Press Enter to exit");
Console.ReadLine();
}
}
If running under Terminal Services, a computer-wide Mutex is ordinarily visible only to applications in the same terminal server session. To make it visible to all terminal server sessions, prefix its name with Global\.
Semaphore
A semaphore is like a nightclub: it has a certain capacity, enforced by a bouncer. Once it’s full, no more people can enter, and a queue builds up outside. Then, for each person that leaves, one person enters from the head of the queue. The constructor requires a minimum of two arguments: the number of places currently available in the nightclub and the club’s total capacity.
A semaphore with a capacity of one is similar to a Mutex or lock, except that the semaphore has no “owner” — it’sthread-agnostic. Any thread can call Release on a Semaphore, whereas with Mutex and lock, only the thread that obtained the lock can release it.
There are two functionally similar versions of this class: Semaphore and SemaphoreSlim. The latter was introduced in Framework 4.0 and has been optimized to meet the low-latency demands of parallel programming. It’s also useful in traditional multithreading because it lets you specify acancellation token when waiting. It cannot, however, be used for interprocess signaling.
Semaphore incurs about 1 microsecond in calling WaitOne or Release; SemaphoreSlim incurs about a quarter of that.
Semaphores can be useful in limiting concurrency — preventing too many threads from executing a particular piece of code at once. In the following example, five threads try to enter a nightclub that allows only three threads in at once:
class TheClub // No door lists!
{
static SemaphoreSlim _sem = new SemaphoreSlim (3); // Capacity of 3
static void Main()
{
for (int i = 1; i <= 5; i++) new Thread (Enter).Start (i);
}
static void Enter (object id)
{
Console.WriteLine (id + " wants to enter");
_sem.Wait();
Console.WriteLine (id + " is in!"); // Only three threads
Thread.Sleep (1000 * (int) id); // can be here at
Console.WriteLine (id + " is leaving"); // a time.
_sem.Release();
}
}
1 wants to enter
1 is in!
2 wants to enter
2 is in!
3 wants to enter
3 is in!
4 wants to enter
5 wants to enter
1 is leaving
4 is in!
2 is leaving
5 is in!
If the Sleep statement was instead performing intensive disk I/O, the Semaphore would improve overall performance by limiting excessive concurrent hard-drive activity.
A Semaphore, if named, can span processes in the same way as a Mutex.
ThreadPool
A thread pool takes away all the need to manage your threads – all you have to do is essentially say “hey! someone should go do this work!”, and a thread in the process’ thread pool will pick up the task and go execute it. And that is all there is to it. Granted, you still have to keep threads from stepping on each other’s toes, and you probably care about when these ‘work items’ are completed – but it is at least a really easy way to queue up a work item.
In fact, working with the ThreadPool is so easy, I’m going to throw all the code at you at once. Below is a pretty simple test app that gives 5 (or NumThreads) work items to the ThreadPool, waits for them all to complete, and then prints out all the answers. I will walk through the code step by step below:
using System.Threading;namespace ThreadPoolTest
{
class Program
{
private const int NumThreads = 5;
private static int[] inputArray;
private static double[] resultArray;
private static ManualResetEvent[] resetEvents;
private static void Main(string[] args)
{
inputArray = new int[NumThreads];
resultArray = new double[NumThreads];
resetEvents = new ManualResetEvent[NumThreads];
Random rand = new Random();
for (int s = 0; s < NumThreads; s++)
{
inputArray[s] = rand.Next(1,5000000);
resetEvents[s] = new ManualResetEvent(false);
ThreadPool.QueueUserWorkItem(new WaitCallback(DoWork), (object)s);
}
Console.WriteLine(“Waiting…”);
WaitHandle.WaitAll(resetEvents);
Console.WriteLine(“And the answers are: “);
for (int i = 0; i < NumThreads; i++)
Console.WriteLine(inputArray[i] + ” -> ” + resultArray[i]);
}
private static void DoWork(object o)
{
int index = (int)o;
for (int i = 1; i < inputArray[index]; i++)
resultArray[index] += 1.0 / (i * (i + 1));
resetEvents[index].Set();
}
}
}
We have three arrays at the top of the program: one for input to the work items (inputArray), one for the results (resultArray), and one for the ManualResetEvents (resetEvents). The first two are self explanatory, but what is aManualResetEvent? Well, it is an object that allows one thread to signal another thread when something happens. In the case of this code, we use these events to signal the main thread that a work item has been completed.
So we initialize these arrays, and then we get to a for loop, which is where we will be pushing out these work items. First, we make a random value for the initial input (cause random stuff is always more fun!), then we create aManualResetEvent with its signaled state initially set to false, and then we queue the work item. Thats right, all you have to do to push a work item out for the ThreadPool to do is call ThreadPool.QueueUserWorkItem.
So what are we queuing here? Well, we are saying that a thread in the thread pool should run the method DoWork, with the argument s. Any method that you want to queue up for the thread pool to run needs to take one argument, an object, and return void. The argument will end up being whatever you passed in as the second argument to theQueueUserWorkItem call – and in this case is the ‘index’ of this work item (the index in the various arrays that it needs to work with). And it makes sense that the method would have to return void – because it isn’t actually returning ‘to’ anything, it is running out there all on its own as a separate thread.
So what are we doing in this DoWork function? Not that much in this case, just a simple summation. The important part is the very last call of the function, which is hit when all the work for this work item is done –resetEvents[index].Set(). This triggers the ManualResetEvent for this work item – signaling the main thread that the work is all done here.
Back up in main thread land, after it has pushed all these work items onto the ThreadPool queue, we hit the very important call WaitHandle.WaitAll(resetEvents). This causes the main thread to block here until all theManualResetEvent objects in the resetEvents array signal. When all of them have signaled, that means that all the work units have been completed, and so we continue on and print out all the results. The results change because we are seeding with random values, but here is one example output:
And the answers are:
3780591 -> 0.991001809831479
3555614 -> 0.991163782231558
2072717 -> 0.989816715560308
2264396 -> 0.989982111762391
544144 -> 0.99066981542858
Pretty simple, eh? There are a couple things to note, though. The default thread pool size for a process is 25 threads, and while you can change this number, this resource is not infinite. If all of the threads in the pool are currently occupied with other tasks, new work items will be queued up, but they won’t get worked on until one of the occupied threads finishes its current task. This generally isn’t a problem unless you are giving the pool very large quantities of work. And really, you should never assume that a task is executed immediately after you queue it, because there is no guarantee of that at all.
That’s it for this intro to thread pools in C#. If there are any questions, leave them below – especially if they push on the more advanced aspects of threads and thread pools (cause then I’ll have an excuse to write some more threading tutorials!).
EventWaitHandler: AutoResetEvent vs. ManualResetEvent
WaitHandler
Threads can communicate using WaitHandlers by signaling. Mutex, Semapore and EventWaitHandle are derived from WaitHandle class.
EventWaitHandle
There are two types of EventWaitHandlers. AutoResetEvent and ManualResetEvent. AutoResetEvent lets one waiting thread at a time when Set() is called but ManualResetEvent lets all waiting threads to pass by when Set() is called. ManualResetEvent starts blocking when Reset() is called.
AutoResetEvent
This acts like a turnstile which lets one at a time. When a thread hits WaitOne(), it waits till some other thread calls Set(). Take a look at the following picture. Thread1, Thread2 and Thread3 are waiting after calling WaitOne(). For every Set() call from another thread, one thread will pass the turnstile.
I have created a simple application to test this. There are two buttons to span a thread DoWork. DoWork has WaitOne call and it blocks threads. Third button calls Set() to release one thread at a time. Click first two buttons to span thread and click third button twice to release blocked threads.
private EventWaitHandle wh = new AutoResetEvent(false);
private void DoWork()
{
Console.WriteLine(Thread.CurrentThread.Name + ": Waiting for Set() notification");
// Wait for notification
//
wh.WaitOne();
Console.WriteLine(Thread.CurrentThread.Name + ": Notified");
}
private void buttonCreateThreadOne_Click(object sender, EventArgs e)
{
Thread a = new Thread(DoWork);
// You can name the thread!.. for debugging purpose
a.Name = "A";
a.Start();
}
private void buttonCreateSecondThread_Click(object sender, EventArgs e)
{
Thread b = new Thread(DoWork);
// You can name the thread!.. for debugging purpose
b.Name = "B";
b.Start();
}
private void buttonReleaseOneThread_Click(object sender, EventArgs e)
{
wh.Set();
}
Please note that the code after WaitOne call in DoWork is not thread safe. A call to Set will let next waiting thread to enter even the first thread is still executing the code.
ManualResetEvent
This is like a gate which lets more than one at a time. When a thread hits WaitOne(), it waits till someother thread calls Set(). Take a look at the following picture. Thread1, Thread2 and Thread3 are waiting after calling WaitOne(). When Set is called from another thread, all waiting thereads will pass the gate.
Code snippet to illustrate the above.
private void buttonFirstThread_Click(object sender, EventArgs e)
{
Thread a = new Thread(DoWork);
// You can name the thread!.. for debugging purpose
a.Name = "A";
a.Start();
}
private void buttonSecondThread_Click(object sender, EventArgs e)
{
Thread b = new Thread(DoWork);
// You can name the thread!.. for debugging purpose
b.Name = "B";
b.Start();
}
private void buttonCallSet_Click(object sender, EventArgs e)
{
wh.Set();
}
private void buttonCallReset_Click(object sender, EventArgs e)
{
wh.Reset();
}
User-defined function in SQL
Functions in programming languages are subroutines used to encapsulate frequently performed logic. Any code that must perform the logic incorporated in a function can call the function rather than having to repeat all of the function logic
CREATE FUNCTION CubicVolume
— Input dimensions in centimeters.
(@CubeLength decimal(4,1), @CubeWidth decimal(4,1),
@CubeHeight decimal(4,1) )
RETURNS decimal(12,3) — Cubic Centimeters.
AS
BEGIN
RETURN ( @CubeLength * @CubeWidth * @CubeHeight )
END
A user-defined function that returns a table can also replace stored procedures that return a single result set. The table returned by a user-defined function can be referenced in the FROM clause of a Transact-SQL statement, whereas stored procedures that return result sets cannot. For example, fn_EmployeesInDept is a user-defined function that returns a table and can be invoked by a SELECT statement:
SELECT *
FROM tb_Employees AS E,
dbo.fn_EmployeesInDept(‘shipping’) AS EID
WHERE E.EmployeeID = EID.EmployeeID
This is an example of a statement that creates a function in the Northwind database that will return a table:
CREATE FUNCTION LargeOrderShippers ( @FreightParm money )
RETURNS @OrderShipperTab TABLE
(
ShipperID int,
ShipperName nvarchar(80),
OrderID int,
ShippedDate datetime,
Freight money
)
AS
BEGIN
INSERT @OrderShipperTab
SELECT S.ShipperID, S.CompanyName,
O.OrderID, O.ShippedDate, O.Freight
FROM Shippers AS S
INNER JOIN Orders AS O ON (S.ShipperID = O.ShipVia)
WHERE O.Freight > @FreightParm
RETURN
END
Difference between Stored Procedure and Functions
1. UDF can be used in the SQL statements anywhere in the WHERE/HAVING/SELECT section where as Stored procedures cannot be.
2. UDFs that return tables can be treated as another rowset. This can be used in JOINs with other tables.
3. Inline UDF’s can be though of as views that take parameters and can be used in JOINs and other Rowset operations.
4. Stored Procedure retuns more than one value at a time while funtion returns only one value at a time.
5. We can call the functions in sql statements (select max(sal) from emp). where as sp is not so.
6. Function do not return the images,text whereas sp returns all.
7. Function and sp both can return the values. But function returns 1 value only. Procedure can return multiple values(max. 1024) we can select the fields from function. in the case of procdure we cannot select the fields.
8. Functions MUST return a value, procedures need not be.
9. You can have DML(insert, update, delete) statements in a function. But, you cannot call such a function in a SQL query.eg: suppose, if u have a function that is updating a table.. you can’t call that function in any sql query.
10. SP can call function but vice-versa not possible.
Clustered and Non-Clustered Index in SQL
1. Introduction
We all know that data entered in the tables are persisted in the physical drive in the form of database files. Think about a table, say Customer (For any leading bank India), that has around 16 million records. When we try to retrieve records for two or three customers based on their customer id, all 16 million records are taken and comparison is made to get a match on the supplied customer ids. Think about how much time that will take if it is a web application and there are 25 to 30 customers that want to access their data through internet. Does the database server do 16 million x 30 searches? The answer is no because all modern databases use the concept of index.
2. What is an Index
Index is a database object, which can be created on one or more columns (16 Max column combination). When creating the index will read the column(s) and forms a relevant data structure to minimize the number of data comparisons. The index will improve the performance of data retrieval and adds some overhead on data modification such as create, delete and modify. So it depends on how much data retrieval can be performed on table versus how much of DML (Insert, Delete and Update) operations.
In this article, we will see creating the Index.
3. First Create Two Tables
To explain these constraints, we need two tables. First, let us create these tables. Run the below scripts to create the tables. Copy paste the code on the new Query Editor window, then execute it.
CREATE TABLE Student(StudId smallint, StudName varchar(50), Class tinyint); CREATE TABLE TotalMarks(StudentId smallint, TotalMarks smallint); Go
Note that there are no constraints at present on these tables. We will add the constraints one by one.
4. Primary Key Constraint
A table column with this constraint is called as the key column for the table. This constraint helps the table to make sure that the value is not repeated and also no null entries. We will mark the StudId column of the Studenttable as primary key. Follow these steps:
- Right click the
studenttable and click on the modify button. - From the displayed layout,
selecttheStudIdrow by clicking the Small Square like button on the left side of the row. - Click on the Set Primary Key toolbar button to set the
StudIdcolumn as primary key column.
Now this column does not allow null values and duplicate values. You can try inserting values to violate these conditions and see what happens. A table can have only one Primary key. Multiple columns can participate on the primary key column. Then, the uniqueness is considered among all the participant columns by combining their values.
5. Clustered Index
The primary key created for the StudId column will create a clustered index for the Studid column. A table can have only one clustered index on it.
When creating the clustered index, SQL server 2005 reads the Studid column and forms a Binary tree on it. This binary tree information is then stored separately in the disc. Expand the table Student and then expand theIndexes. You will see the following index created for you when the primary key is created:
With the use of the binary tree, now the search for the student based on the studid decreases the number of comparisons to a large amount. Let us assume that you had entered the following data in the table student:
The index will form the below specified binary tree. Note that for a given parent, there are only one or two Childs. The left side will always have a lesser value and the right side will always have a greater value when compared to parent. The tree can be constructed in the reverse way also. That is, left side higher and right side lower.
Now let us assume that we had written a query like below:
Select * from student where studid = 107;
Execution without index will return value for the first query after third comparison.
Execution without index will return value for the second query at eights comparison.
Execution of first query with index will return value at first comparison.
Execution of second query with index will return the value at the third comparison. Look below:
- Compare 107 vs 103 : Move to right node
- Compare 107 vs 106 : Move to right node
- Compare 107 vs 107 : Matched, return the record
If numbers of records are less, you cannot see a different one. Now apply this technique with a Yahoo email user accounts stored in a table called say YahooLogin. Let us assume there are 33 million users around the world that have Yahoo email id and that is stored in the YahooLogin. When a user logs in by giving the user name and password, the comparison required is 1 to 25, with the binary tree that is clustered index.
Look at the above picture and guess yourself how fast you will reach into the level 25. Without Clustered index, the comparison required is 1 to 33 millions.
Got the usage of Clustered index? Let us move to Non-Clustered index.
6. Non Clustered Index
A non-clustered index is useful for columns that have some repeated values. Say for example, AccountTypecolumn of a bank database may have 10 million rows. But, the distinct values of account type may be 10-15. Aclustered index is automatically created when we create the primary key for the table. We need to take care of the creation of the non-clustered index.
Follow the steps below to create a Non-clustered index on our table Student based on the column class.
- After expanding the
Studenttable, right click on theIndexes. And click on the New Index.
- From the displayed dialog, type the index name as shown below and then click on the Add button to select the column(s) that participate in the index. Make sure the
Indextype is Non-Clustered.
- In the select column dialog, place a check mark for the column class. This tells that we need a non-clusteredindex for the column
Student.Class. You can also combine more than one column to create theIndex. Once the column is selected, click on the OK button. You will return the dialog shown above with the selected column marked in blue. Our index has only one column. If you selected more than one column, using theMoveUpandMoveDownbutton, you can change order of the indexed columns. When you are using the combination of columns, always use the highly repeated column first and more unique columns down in the list. For example, let use assume the correct order for creating the Non-clustered index is:Class,DateOfBirth,PlaceOfBirth.
- Click on the Index folder on the right side and you will see the non-clustered index based on the column class is created for you.
7. How Does a Non-Clustered Index Work?
A table can have more than one Non-Clustered index. But, it should have only one clustered index that works based on the Binary tree concept. Non-Clustered column always depends on the Clustered column on the database.
This can be easily explained with the concept of a book and its index page at the end. Let us assume that you are going to a bookshop and found a big 1500 pages of C# book that says all about C#. When you glanced at the book, it has all beautiful color pages and shiny papers. But, that is not only the eligibility for a good book right? One you are impressed, you want to see your favorite topic of Regular Expressions and how it is explained in the book. What will you do? I just peeped at you from behind and recorded what you did as below:
- You went to the Index page (it has total 25 pages). It is already sorted and hence you easily picked up Regular Expression that comes on page Number 17.
- Next, you noted down the number displayed next to it which is 407, 816, 1200-1220.
- Your first target is Page 407. You opened a page in the middle, the page is greater than 500.
- Then you moved to a somewhat lower page. But it still reads 310.
- Then you moved to a higher page. You are very lucky you exactly got page 407. [Yes man you got it. Otherwise I need to write more. OK?]
- That’s all, you started exploring what is written about Regular expression on that page, keeping in mind that you need to find page 816 also.
In the above scenario, the Index page is Non-Clustered index and the page numbers are clustered index arranged in a binary tree. See how you came to the page 407 very quickly. Your mind actually traversed the binary tree way left and right to reach the page 407 quickly.
Here, the class column with distinct values 1,2,3..12 will store the clustered index columns value along with it. Say for example; Let us take only class value of 1. The Index goes like this:
So here, you can easily get all the records that have value for class = 1. Map this with the Book index example now.
Inversion Of Control(IOC) or Dependency Injection(DI)?
In designing an object-oriented application, a major tenet of design is “loose coupling”. Loosely, not meant for the pun, “loose coupling” means that objects should only have as many dependencies as is needed to do their job – and the dependencies should be few. Furthermore, an object’s dependencies should be on interfaces and not on “concrete” objects, when possible. (A concrete object is any object created with the keyword new.) Loose coupling promotes greater reusability, easier maintainability, and allows you to easily provide “mock” objects in place of expensive services, such as a socket-communicator. “Dependency Injection” (DI), also more cryptically known as “Inversion of Control” (IoC), can be used as a technique for encouraging this loose coupling. There are two primary approaches to implementing DI: constructor injection and setter injection. Obviously, at some point, something must be responsible for creating the concrete objects that will be injected into another object. The injector can be a parent object, which I’ll call the “DI controller”, or can be externalized and handled by a “DI container” framework. What follows is a brief overview of the various approaches for using dependency injection techniques.
Constructor Injection
Constructor Injection is the DI technique of passing an object’s dependencies to its constructor. The below example includes a class, Customer, that exposes a method for retrieving every sales-order that the customer made on a particular date. Consequently, the Customer class needs a data-access object for communicating with the database. Assume, an OrderDao (“order data-access object”) exists which implements the interface IOrderDao. One way that a Customer object can get this dependency is by executing the following within the: IOrderDao orderDao = new OrderDao();. The primary disadvantage of this is two-fold:
1. the benefit of having the interface in the first place has been negated since the concrete instance was created locally, and
2. OrderDao cannot easily be replaced by a mock object for testing purposes. (Mock objects will be discussed shortly.)
The aforementioned example follows:
public class Customer {
public Customer(IOrderDao orderDao) {
if (orderDao == null)
throw new ArgumentNullException(“orderDao may not be null”);
this.orderDao = orderDao;
}
public IList GetOrdersPlacedOn(DateTime date) {
// … code that uses the orderDao member
// get orders from the datasource …
}
private IOrderDao orderDao;
}
In the example, note that the constructor accepts an interface; it does not accept a concrete object. Also, note that an exception is thrown if the orderDao parameter is null. This emphasizes the importance of receiving a valid dependency. Constructor Injection is, in my opinion, the preferred mechanism for giving an object its dependencies. It is clear to the developer invoking the object which dependencies need to be given to the Customer object for proper execution. But consider the following example… Suppose you have a class with ten methods that have no dependencies, but you’re adding a new method that does have a dependency on IOrderDao. You could change the constructor to use Constructor Injection, but this may force you to change constructor calls all over the place. Alternatively, you could just add a new constructor that takes the dependency, but then how does a developer easily know when to use one constructor over the other. Finally, if the dependency is very expensive to create, why should it be created and passed to the constructor when it may only be used rarely? “Setter Injection” is another DI technique that can be used in situations such as this.
Setter Injection
Setter Injection does not force dependencies to be passed to the constructor. Instead, the dependencies are set onto public properties exposed by the object in need. As implied previously, the primary motivators for doing this include:
1. supporting dependency injection without having to modify the constructor of a legacy class, and
2. allowing expensive resources or services to be created as late as possible and only when needed.
The code below modifies the Constructor Injection example to use
Setter Injection instead:
public class Customer {
public Customer() {}
public IOrderDao OrderDao {
set { orderDao = value; }
get {
if (orderDao == null)
throw new MemberAccessException(“orderDao” +
” has not been initialized”);
return orderDao;
}
}
public IList GetOrdersPlacedOn(DateTime date) {
//… code that uses the OrderDao public
//… property to get orders from the datasource …
}
// Should not be called directly;
// use the public property instead
private IOrderDao orderDao;
}
In the above example, the constructor accepts no arguments. Instead, the invoking object is responsible for setting the IOrderDao dependency before the method GetOrdersPlacedOn is called. With Constructor Injection, an exception is thrown if the dependency is not set immediately, i.e., upon creation. With Setter Injection, an exception isn’t thrown until a method actually attempts to use the dependency. Make note of the fact that GetOrdersPlacedOn uses the public OrderDao property; it does not call the private orderDao directly. This is so that the getter method has an opportunity to validate if the dependency has yet been initialized. Setter Injection should be used sparingly in place of Constructor Injection, because it:
1. does not make it clear to the developer which dependencies are needed when, at least until a “has not been initialized” exception is thrown, and
2. makes it a bit more difficult to track down where the exception came from and why it got thrown. With this said, Setter Injection can save on modifying a lot of legacy code when introducing new methods, and can provide a performance boost if the dependency is expensive or not easily accessible.
The Injectors
The next logical question is, what actually creates the dependencies that are to be injected into “injectees”? There are two appropriate places for adding creation logic: controllers and containers.
DI Controllers
The “DI controller” approach is the simpler to understand and implement. In a properly tiered architecture, an application has distinct layers for handling logic. The simplest layering usually consists of a data-layer for talking to the database, a presentation-layer for displaying the UI, and a domain-logic layer for performing business logic. A “controller” layer always exists, even if not well defined, for coordinating UI events to the domain and data layers, and vice versa. For example, in ASP.NET, the code-behind page acts as a rudimentary controller layer. More formalized controller-layer approaches exist: Struts and Spring for Java; Front Controller and Spring .NET for .NET. All of these approaches follow some form of variant of the Model-View-Controller pattern. Regardless of what you use as your controller, the controller is an appropriate location for performing Dependency Injection “wiring”. This is where concrete objects are created and injected as dependencies. What follows are two examples of DI performed by a controller. The first is an illustrative example of “production code” – code that you’d end up deploying. The second is an example of “test code” – code that’s used to test the application, but is not deployed and does not have the need to have a live database. Controller code performing the dependency injection (e.g., from an ASP.NET code-behind page):
//… code performed when the controller is loaded …
IOrderDao orderDao = new OrderDao();
// Using Setter Injection on a pre-existing customer
someCustomer.OrderDao = orderDao;
IList ordersPlacedToday =
someCustomer.GetOrdersPlacedOn(DateTime.Now);
…
Unit-test code performing dependency injection:
IOrderDao orderDao = new MockOrderDao();
// Using Setter Injection on a pre-existing customer
someCustomer.OrderDao = orderDao;
IList ordersPlacedToday =
someCustomer.GetOrdersPlacedOn(DateTime.Now);
One of the major benefits of using a DI-controller to inject dependencies is that it’s straightforward and easy to point to where the creation is occurring. The drawback to using DI-controllers is that the dependencies are still hard-coded somewhere; albeit, they’re hard-coded in a location that is often subject to frequent changes anyway. Another drawback is that now the DI-controllers themselves can’t be easily unit-tested with mock objects. (Granted, a powerful tool such as TypeMock can do just about anything when it comes to injecting mock objects. But a tool such as TypeMock should be used only when absolutely necessary as it can lead to habits of not programming-to-interface. In fact, I’d recommend only considering the use of it on very difficult to test, legacy applications.) In ASP.NET, I prefer to use the Model-View-Presenter (MVP) pattern, and have the ASP.NET code-behind page create dependencies and inject them to the presenter via Construction Injection. Additionally, I use UserControls as the View part of the pattern, so the ASP.NET code-behind acts purely as an MVP “dependency initializer” between the UserControls (View) and their presenters. Another option to implementing constructor or setter DI is the use of an application container…
DI Containers
Inversion-of-Control/Dependency-Injection “containers” can be used to watch an application and inject dependencies whenever a particular event occurs. For example, whenever a Customer instance is created, it automatically gets injected with its needed dependencies. It’s a strange concept at first, but can be useful for managing large applications with many service dependencies. Different container providers each have their own mechanism for managing dependency injection settings.
A very good example can be found at :
http://www.codeproject.com/Articles/26466/Dependency-Injection-using-Spring-NET/
http://www.youtube.com/watch?v=Jjp_EYEn4bc&feature=related
http://www.youtube.com/watch?v=IOZzxmJVus0&feature=relmfu
http://joelabrahamsson.com/entry/inversion-of-control-introduction-with-examples-in-dotnet
Singleton Class
using System;
public sealed class Singleton
{
private static volatile Singleton instance;
private static object syncRoot = new Object();
private Singleton() {}
public static Singleton Instance
{
get
{
if (instance == null)
{
lock (syncRoot)
{
if (instance == null)
instance = new Singleton();
}
}
return instance;
}
}
}
This approach ensures that only one instance is created and only when the instance is needed. Also, the variable is declared to be volatile to ensure that assignment to the instance variable completes before the instance variable can be accessed. Lastly, this approach uses a syncRoot instance to lock on, rather than locking on the type itself, to avoid deadlocks.
This double-check locking approach solves the thread concurrency problems while avoiding an exclusive lock in every call to the Instance property method. It also allows you to delay instantiation until the object is first accessed.
Real World Example of a Singleton Class
Thread pools, SQL Connection Pools, Registry objects, Objects handling user preferences, Caches, Factory classes, Builder classes and Statistics utilities like a hit counter, log4net, when you call its logger, it uses a singleton class to return it.
Difference between Singleton and Static Class
Another question that usually comes up when it comes to using a Singleton is “Why not just use a static class?”. Static classes still have many uses and lots of times, people get confused and will use a Singleton as much as possible. One easy rule of thumb you can follow is if it doesn’t need to maintain state, you can use a Static class, otherwise you should use a Singleton.
So here is a quick list of uses for static classes:
Math.pow(double a, double b);
Interger.parseInt(String s);
Interger.toString(int i);
As you can see, the state of these methods don’t matter. You just want to use them to perform a simple task for you. But if you coding your application and you are using a central object where state does matter(such as the ModelLocator example), then its best to use a Singleton.
The next reason you may want to use a Singleton is if it is a particularly “heavy” object. If your object is large and takes up a reasonable amount of memory, you probably only one of those objects floating around. This is the case for things like a if you have a factory method that is particularly robust, you want to make sure that its not going to be instantiated multiple times. A Singleton class will help prevent such the case ever happening.
Thread Management
Download MultiThreading in .NET 2.0
Why Threads?
Some years ago I saw a letter-to-the-editor in response to the need of a multitasking system, the writer said “I don’t care about multitasking because I can only do one thing at a time.” Really? Does this person only do one thing at a time? This person continues with “I finish my Word document, print it, fire up my modem to connect to the Internet, read my e-mail, and go back to work on another document.” Does this person efficiently use his time? Many of us might suggest that this person could fire up his modem while the printer is printing, or work on another document while the previous one is being printed. Good suggestions, indeed. In fact, we are multitasking many tasks in our daily life. For example, you might watch your favorite TV program or movie and enjoy your popcorn. Or, while you are printing a long document, you might read a newspaper or company news. There are so many such examples demonstrating that we are doing two or more tasks simultaneously. This is a form of multitasking! In fact, multitasking is more common in industry. While each worker of an assembly line seems working in a sequential way, there could be multiple production lines, all of which perform the same task concurrently. Moreover, the engine assembly lines produce engines while the other lines produce other components. Of course, the car assembly lines run concurrently with all of the other lines. The final product is the result of these concurrently running assembly/production lines. Without this type of “parallelism” Detroit would not be able to produce sufficient airplanes and tanks for WW II and enough number of automobiles to fulfill our demand.
Unfortunately, before you learn how to split your program into multiple execution threads, all programs you wrote contain a single execution thread. The following diagram shows an example. Suppose we have a program of two parts, Part A and Part B. After Part A finishes its computation, we use some cout statements to print out a large amount of output. As we all know, when a program prints, the control is transfered to a function in C++’s library and the execution of that program is essentially suspended, shown in dashed line in the diagram, until the printing completes. Once this (i.e., printing) is done, the execution of the program resumes and starts the computation of Part B. Is there anything wrong with this? No, we are used to it and we are trained to do programming in this way ever since CS101. However, is this way of programming good enough in terms of efficiency? It depends; but, in many situations, it is not good enough.
If Part B must use some data generated by Part A, then Part B perhaps has to be executed after the output of cout completes. On the other hand, in many situations, Part A and Part B are independent of each other, or one may slightly rewrite both parts so that they do not depend on each other. In this case, Part B does not have to wait until cout completes. In fact, this is the key point! Therefore, before the execution of Part A, the program can be split into two execution threads, one for Part A and the other for Part B. See the diagram below. In this way, both execution threads share the CPU and all resources allocated to the program. Moreover, while Part A is performing the output which causes Part A to wait, Part B can take the CPU and executes. As a result, this version is more efficient than the previous one. Moreover, in a system with more than one CPUs, it is possible that the system will run both Part A and Part B at the same time, one on each CPU.
In real programming practice, a program may use an execution thread for handling keyboard/mouse input, a second execution thread for handling screen updates, and a number of other threads for carrying out various computation tasks.
Example: Quicksort
The quicksort algorithm consists of two steps in each recursion. First, the partition step divides the input array segment into two segments such that all elements in the left segment is smaller or equal to all elements in the right segment. Second, the sorting step simply sorts the left segment and the right segment. After these two steps complete, the input segment is sorted. While it is not so obvious if the partition step can have multiple execution threads, one can split the execution of the sorting step into two, one for sorting the left segment while the other for sorting the right one. This is shown in the diagram below:
Example: Merging
Consider another simple problem. Suppose we have two arrays a[ ] and b[ ] of n elements each. For simplicity, we assume that all of these 2n elements are different. Our job is to merge these two arrays into a sorted one. Everyone who took a data structures course knows how to do it; however, let us look at the same problem from a different angle.
Take an element from array a, say a[i]. We know that it is larger than i-1 elements of a. If we can figure out how many elements of b that are smaller than a[i], we will be able to know the exact location of a[i] in the sorted array. This is illustrated in the following diagram:
With a slightly modified binary search, we can easily determine the location of a[i] in array b. There are only three possibilities:
- a[i] is less than b[0]: In this case, a[i] is larger than i-1 elements in a and smaller than all elements in b. Therefore, a[i] should be in position i of the sorted array.
- a[i] is larger than b[n]: In this case, a[i] is larger than i-1 elements in a and n elements in b. Therefore, a[i] should be in position i+n of the sorted array.
- a[i] is between b[k-1] and a[k]. In this case, a[i] is larger than i-1 elements in a and k-1 elements in b. Therefore, a[i] should be in position i+k-1 of the sorted array.
After the main program reads in both arrays, it can split itself into 2n execution threads, each of which handles an element in a or in b. Each of these execution threads determines its position in the merged array and writes the values into the corresponding location. After this, we will have a merged array! Thus, we use 2n threads, each of which takes O(log2(n)) comparisons to get the job done. In the conventional serial case, we use one execution thread which uses O(n) comparisons to merge the arrays.
Example: Matrix Multiplication
Another interesting application is the multiplication of two matrices. Suppose we have two matrices Am×k (m rows and k columns) and Bk×n (k rows and n columns) and want to compute the product of A and B into a matrix C of m rows and n columns. The entry of C on row i and column j is the sum of the products of the corresponding elements on row i of matrix A and column j of matrix B as shown below:
How can we use multiple execution threads to solve this problem? We notice that the computation of Ci,j is independent of the computation of any other entries of matrix C. Because of this, after matrices A and B are read in, the main program can split m×n execution threads, one for each entry of matrix C. Each of these execution threads computes the products of the corresponding elements, sums them up, and stores the result into matrixC.
It requires k multiplications to compute a single entry of matrix C. Since there are m×n entries in C, the program with only one thread uses m×n×k multiplications. On the other hand, in the above scheme, each thread uses kmultiplications and there are m×n threads. If we have only one CPU, the multiple execution threads version may not be as efficient as the single execution thread one; however, if there are more than one CPUs, each of these CPUs may be assigned to a number of execution threads and the execution efficiency is higher. In the extreme case in which we have m×n CPUs to use, because all execution threads run at the same time, it only takes the time to compute one entry to complete the whole matrix multiplication. Thus, it is m×n times more efficient than the single execution thread version.
By now, you perhaps have had a good feeling of why splitting a program into multiple execution threads may increase the execution efficiency. However, just like in the movie Multiplicity, creating too many execution threads may lead to a chaotic situation because in addition to splitting a program into multiple execution threads these threads must communicate with each other properly in order to work together. Thus, in addition to learning the way of creating execution threads, we also have to learn the way of managing threads and the way of thread synchronization.
The above examples may look a little unrealistic and their benefits seem only about program efficiency. There are other benefits of using multiple execution threads.
There are four basic thread management operations: thread creation, thread termination, thread join, and thread yield.
Thread Creation
We have discussed the creation of threads in a above page. Basically, we can split the execution thread into two. After this, both threads execute concurrently. The creating thread is the parent thread, and the created thread is a child thread. Note that any thread, including the main program which is run as a thread when it starts, can create child threads at any time. In the following diagram, Thread A runs initially. Sometime later, it creates Thread B as indicated by a yellow dot. After this creation, Thread A and Thread B runs concurrently. Later on, Thread A may create one more thread Thread C. After Thread C is created, there are three threads running concurrently, all of which compete to use the CPUs. However, which thread is run at a particular time is not known to any one of them. The quicksort example discussed on a above page employs this scheme, where Thread A receives an array segment, partitions it into two segments, creates Thread B to sort the left segment, and then creates Thread C to sort the right one. Or, after the given array segment is partitioned into two, Thread A creates Thread B to sort the left segment and sorts the right segment by itself. In this way, two threads, one parent – Thread A – and one child – Thread B – would be sufficient.
In the matrix multiplication example, the main thread (i.e., the main program) must create a number of threads, one for each entry of the resulting matrix. A possibility is shown below. Two for statements are used to create m×n threads. We shall see more examples that dynamically create threads later.
Thread Termination
For most of the cases, threads are not created and run forever. After finish their work, threads terminate. In the quicksort example, after both array subsegments are sorted, the threads created for sorting them terminate. In fact, the thread that creates these two child threads terminates too, because its assigned task completes. In the merging example, the threads created to determine the position of array elements a[i] and b[j] in the merged array terminate once the final positions are computed. Similarly, in the matrix multiplication example, once the value of C[i,j] is computed, the corresponding thread terminates. In general, when the assigned task of a thread completes, the thread may be terminated.
Moreover, if the parent thread terminates, all of its child threads terminate as well. Why is this important? We briefly mentioned in a above page that the child threads share resources with the parent thread, including variables. When the parent thread terminates, all of its variables are gone, and, as a result, the child threads will not be able to access to those resources that the parent thread owns. Thus, if the parent thread runs faster and terminates earlier than its child threads do, we have a problem! This is why we need the third thread management feature: thread join.
Thread Join
Imagine the following scenario. You are preparing for tomorrow’s final examine and feel a little hungry. So, you give your younger brother ten bucks and ask him to buy a pizza for you. In this case, you are the main thread and your brother is a child thread. Once your order is given, both you and your brother are doing their job concurrently (i.e., studying and buying a pizza). Now, we have two cases to consider. First, your brother brings your pizza back and terminates while you are studying. In this case, you can stop studying and enjoy the pizza. Second, you finish your study early and sleep (i.e., your assigned job for today – study for tomorrow’s final exam – is done) before the pizza is available. Of course, you cannot sleep; otherwise, you won’t have a chance to eat the pizza. What you are going to do is to wait until your brother brings the pizza back. This is exactly the problem and solution we mentioned at the end of the previous section.
Thread join is designed to solve this problem. A thread can execute a thread join to wait until the other thread terminates. In our case, you – the main thread – should execute a thread join waiting for your brother – a child thread – to terminate. In general, thread join is for a parent to join with one of its child threads. Thread join has the following activities, assuming that a parent thread P wants to join with one of its child threads C.
- When P executes a thread join in order to join with C, which is still running, P is suspended until C terminates. Once C terminates, P resumes.
- When P executes a thread join and C has already terminated, P continues as if no such thread join has ever executed (i.e., join has no effect).
A parent thread may join with many child threads created by the parent. Or, a parent only join with some of its child threads, and ignore other child threads. In this case, those child threads that are ignored by the parent will be terminated when the parent terminates.
Thread Yield
Suppose you run a number of programs at the same time on a computer. It is possible that some CPU hogs keep eating up the CPU cycles so that other programs may hardly run. Well, this may be a problem of the scheduling policy of the operating system. However, when we write our programs with multiple threads, we have to make sure that some threads will not occupy the CPU forever, or for a very long time, without relinquishing it. Otherwise, we will end up in the situation where one or two threads keep running while the others simply wait there for their turns. That is, we run our threads in a very “polite” way that once a while a thread takes some rest so that the CPU can be used by other threads. This is achieved by thread yield.
When a thread executes a thread yield, the executing thread is suspended and the CPU is given to some other runnable thread. This thread will wait until the CPU becomes available again. Technically, in process scheduler’s terminology, the executing thread is put back into the ready queue of the processor and waits for its next turn. The following shows an example, where a small circle indicates the execution of a thread yield, a small square means the control is transferred back, a solid arrow indicates thread execution, and a dashed line segment depicts a thread waiting for execution. Suppose we have three threads A, B and C. Initially, A is running and executes a thread yield sometime later. This causes A is suspended temporarily and the CPU is given to the next thread, say B. Then, B runs for a while and executes a thread yield. Because there are two threads that are ready to run, A and C, the thread system picks one to run. Suppose it is C. When C executes a thread join, the control may switch back to A or B; however, the diagram shows the control is given back to A. In this way, threads execute in a cooperative way.
Thread Suspend and Resume
Thread suspend and resume are two more thread management features. When a thread executes a thread suspend to suspend the execution of itself or another thread, the indicated thread will be suspended until the execution of a thread resume that releases the indicated thread. For example, suppose we have three threads A, B and C running concurrently. Then, thread A execute a thread suspend to suspend the execution of threadB. After this, we have only two threads A and C running concurrently. Note that even though both A and C are waiting for the completion of their own I/O activities and no thread is running, the suspended thread B cannot run. To run thread B again, one of the other threads must execution a corresponding thread resume. For example, thread C may execute a thread resume to resume thread B‘s execution. After this, all three threads are running concurrently.
Both thread yield and thread suspend cause the execution of a thread to be suspended. What is the difference? The difference is a big one! With thread yield, the yielding thread is put back to the ready queue and will run when its turn comes. Thus, a yielding thread is runnable if the CPU becomes free in the future, although it is suspended. With a thread suspend, the suspended thread is not in the ready queue, and, as a result, the scheduler will not be able to pick it up and let it run when the CPU becomes free. Instead, the execution of a suspended thread can be resumed only by a specific thread resume call.
Thread suspend/resume can be very useful. For example, suppose a program must handle five different tasks. The main program may create five threads, one for each task. Initially, all threads are suspended by the main program. Once a task comes, the main program just resumes the corresponding thread. After handling the task, the thread simply suspends itself. This may be more efficient that creating a new thread to handle the task and then terminating the thread. However, thread suspend and resume could post some problem. Suppose a thread acquire a lock so that it becomes the only thread that can access to a shared resource. If before the thread releases the lock, it is suspended by another thread. Should this happen, no other thread can access the shared resource until a thread resume the suspended thread for it to release the lock. Because of this potential problem, which may lead to a system deadlock, the use of thread suspend and resume is usually not recommended. Some systems such as the Pthread do not support thread suspend and resume.
What is difference between Daemon and Non Daemon Thread
In java we have two type of Threads :
Daemon Thread and User Threads. Generally all threads created by programmer are user thread (unless you specify it to be daemon or your parent thread is a daemon thread). User thread are generally meant to run our programm code. JVM doesn’t terminates unless all the user thread terminate.
On the other hand we have Daemon threads. These threads are generally ‘Service provider’ threads. They should not be used to execute your program code but system code. These thread run in parallel to your code but JVM can kill them anytime. When JVM finds no user threads it stops and all daemon thread terminate instantly. Thus you should never depend on daemon thread to perform any program code.
Events with Threading
Use events with thread; this is one of the techniques to synchronize one thread with other like ManualResetEvent
Difference between a computer process and thread
A single process can have multiple threads that share global data and address space with other threads running in the same process, and therefore can operate on the same data set easily. Processes do not share address space and a different mechanism must be used if they are to share data.
If we consider running a word processing program to be a process, then the auto-save and spell check features that occur in the background are different threads of that process which are all operating on the same data set (your document).
Process
In computing, a process is an instance of a computer program that is being sequentially executed[1] by a computer system that has the ability to run several computer programs concurrently.
Thread
A single process may contain several executable programs (threads) that work together as a coherent whole. One thread might, for example, handle error signals, another might send a message about the error to the user, while a third thread is executing the actual task
Interlocked class
Provides atomic operations for variables that are shared by multiple threads. Interlocked class provides methods by which you can achieve following functionalities :-
1. increment Values.
2. Decrement values.
3.Exchange values between variables.
4.Compare values from any thread.
in a synchronization mode.
Example :- System.Threading.Interlocked.Increment(IntA)
Using Statement
Defines a scope, outside of which an object or objects will be disposed.
using (Font font1 = new Font(“Arial”, 10.0f))
{
}
C#, through the .NET Framework common language runtime (CLR), automatically releases the memory used to store objects that are no longer required. The release of memory is non-deterministic; memory is released whenever the CLR decides to perform garbage collection. However, it is usually best to release limited resources such as file handles and network connections as quickly as possible.
The using statement allows the programmer to specify when objects that use resources should release them. The object provided to the using statement must implement theIDisposable interface. This interface provides the Dispose method, which should release the object’s resources.
A using statement can be exited either when the end of the using statement is reached or if an exception is thrown and control leaves the statement block before the end of the statement.
using System;
class C : IDisposable
{
public void UseLimitedResource()
{
Console.WriteLine(“Using limited resource…”);
}
void IDisposable.Dispose()
{
Console.WriteLine(“Disposing limited resource.”);
}
}
class Program
{
static void Main()
{
using (C c = new C())
{
c.UseLimitedResource();
}
Console.WriteLine(“Now outside using statement.”);
Console.ReadLine();
}
}
Output:
Using limited resource…
Disposing limited resource.
Now outside using statement.
Difference Between Finalize and Dispose Method
.NET Framework provides two methods Finalize and Dispose for releasing unmanaged resources like files, database connections, COM etc. This article helps you to understand the difference between Finalize and Dispose method.
Finalize vs dispose method
Implementing Finalize method (with dispose())
If you want to implement Finalize method, it is recommended to use Finalize and Dispose method together as shown below:
// Using Dispose and Finalize method together
public class MyClass : IDisposable
{
private bool disposed = false;
//Implement IDisposable.
public void Dispose()
{
Dispose(true);
GC.SuppressFinalize(this);
}
protected virtual void Dispose(bool disposing)
{
if (!disposed)
{
if (disposing)
{
// TO DO: clean up managed objects
}
// TO DO: clean up unmanaged objects
disposed = true;
}
}
//At runtime C# destructor is automatically Converted to Finalize method
~MyClass()
{
Dispose(false);
}
}
Note
- It is always recommended to use Dispose method to clean unmanaged resources. You should not implement the Finalize method until it is extremely necessary.
- At runtime C#, C++ destructors are automatically Converted to Finalize method. But in VB.NET you need to override Finalize method, since it does not support destructor.
- You should not implement a Finalize method for managed objects, because the garbage collector cleans up managed resources automatically.
- A Dispose method should call the GC.SuppressFinalize() method for the object of a class which has destructor because it has already done the work to clean up the object, then it is not necessary for the garbage collector to call the object’s Finalize method.
Design Patterns
Design patterns are recurring solutions to software design problems you find again and again in real-world application development. Patterns are about design and interaction of objects, as well as providing a communication platform concerning elegant, reusable solutions to commonly encountered programming challenges.
The Gang of Four (GoF) patterns are generally considered the foundation for all other patterns. They are categorized in three groups: Creational, Structural, and Behavioral. Here you will find information on these important patterns.
To give you a head start, the C# source code is provided in 2 forms: ‘structural’ and ‘real-world’. Structural code uses type names as defined in the pattern definition and UML diagrams. Real-world code provides real-world programming situations where you may use these patterns.
A third form, ‘.NET optimized’ demonstrates design patterns that exploit built-in .NET 4.0 features, such as, generics, attributes, delegates, object and collection initializers, automatic properties, and reflection.
| Creational Patterns | |
| Abstract Factory | Creates an instance of several families of classes |
| Builder | Separates object construction from its representation |
| Factory Method | Creates an instance of several derived classes |
| Prototype | A fully initialized instance to be copied or cloned |
| Singleton | A class of which only a single instance can exist |
| Structural Patterns | |
| Adapter | Match interfaces of different classes |
| Bridge | Separates an object’s interface from its implementation |
| Composite | A tree structure of simple and composite objects |
| Decorator | Add responsibilities to objects dynamically |
| Facade | A single class that represents an entire subsystem |
| Flyweight | A fine-grained instance used for efficient sharing |
| Proxy | An object representing another object |
| Behavioral Patterns | |
| Chain of Resp. | A way of passing a request between a chain of objects |
| Command | Encapsulate a command request as an object |
| Interpreter | A way to include language elements in a program |
| Iterator | Sequentially access the elements of a collection |
| Mediator | Defines simplified communication between classes |
| Memento | Capture and restore an object’s internal state |
| Observer | A way of notifying change to a number of classes |
| State | Alter an object’s behavior when its state changes |
| Strategy | Encapsulates an algorithm inside a class |
| Template Method | Defer the exact steps of an algorithm to a subclass |
| Visitor | Defines a new operation to a class without change |
A good explanation can be found at : http://www.dotnetuncle.com/Design-Patterns/dot-net-design-pattern-interview-questions.aspx
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