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SQL stands for Structured Query Language and is a standardized programming language used to perform multiple tasks on data and manage relational databases. SQL is easy to use and understands that it has replaced many NoSQL programming languages in the technical space. Today, popular frameworks had their programming languages too. For example, Hadoop has its SQL language and many other platforms are based on the same concept.
We cannot say that SQL is the universal programming language for relational databases. Since the time of its inception, SQL has had certain strikes against it. Many developers and researchers believed that SQL will not work well except for production databases but they were wrong. Today, SQL is used everywhere and runtime performance in the case of SQL is too high.
When SQL was not introduced in the market, there were navigational programming interfaces that were typically designed around the network schema called the Codasyl data model. This data model was responsible for the Cobol programming language and other database extensions too. In the case of Cobol, the records were navigated through sets to express one-to-many relationships. In the case of hierarchical databases, only one record is allowed to be attached with one data set only. In the case of network databases, you can enjoy working with one-to-many and many-to-many relationships. Earlier, programming was quite boring and time-consuming too. The launch of SQL gives a new boost to database performance and today skilled SQL professionals are needed everywhere. Almost every database programmer believes that SQL is quite efficient during both execution and runtime. You can play with data as per your terms and conditions. Even memory consumption is very low when compared to non-relational databases that were used in the past.
Would you like to double the execution speed and memory? If yes, there are two major reasons for the same like portability and ease of development. In 1980, execution speed and memory consumption were not given much importance but as computer hardware improved and became affordable then people focused more on execution speed, memory, and cost of development too.
In simple words, Codasyl databases are also based on the relational database model but improvement in development time was quite significant and portability of SQL turned out to be a pipe dream here. So, what was the reason behind the discovery of SQL? In IBM, there was a scientist who was majorly working on relational model theory and how to publish it. Soon, the IBM team also started supporting the scientist and soon there was a programming language called SQL and soon it was integrated with the Oracle database too. In 1980, SQL became an international trademark and started using it everywhere.
Now, Oracle and IBM both started supporting the development of SQL. Soon, the language got support from customers as well. Initially, this was not easy hiring or training Codasyl programmers or developers, so SQL became a highly attractive option in this situation. In the late 1980s, developers stapled a SQL query processor on the top of Codasyl databases where they realized that relational databases should be designed from scratch to make them more relational.
Since that time, the inception of relational databases came into existence. This was a purely relational database system where tuples were grouped into relations and they are consistent with first-order predicate logic too. For real-world relational databases, there are tables, fields, triggers, constraints, primary keys, foreign keys, etc. SQL helps you in playing with the data where you can filter data and access desired outputs at your fingertips. Further, there is one SQL query processor and the query optimizer to turn SQL declarations into a query plan that can be executed with the database engine. Here, SQL is the sub-language defining schemas, DDL (Data definition language), helps in modifying data, DML (Data Manipulation Language), etc. You could understand the concept closely with SQL declare queries, SELECT statements or relational joins, etc. In the next section, we will focus on the Select statement, how to use the SELECT statement in the SQL.
The SELECT statement in SQL tells the query optimizer what output could be returned, what should be found in tables, what relations should be followed, or what order should be followed for the return data. The query optimizer can figure out what indexes should be used for an excellent table scan and achieve the maximum query performance unless the particular database supports index hints.
The major part of the relational databases is designed on the judicial usage of indexes. If you want to use an index to perform frequent queries then database performance will slow down under heavy road loads. In case you had too many indexes, then again database performance will get affected due to heavy write and update loads.
Another fact to focus on here is deciding on the unique primary key for each table. The Primary key is a set of the column having unique values and it should not be NULL. The impact of primary keys should be considered in common queries too but how to perform joins when it is used as the foreign key in any other table. Also, you need to check how it will affect the data locality of references.
The case of advanced database tables that are broken down into multiple fields also depends on the value of the primary key either horizontally or vertically. For example, when you want to distribute the particular primary key across volumes then you don't have to use data stamps or consecutive integers as primary keys. The SELECT statement in SQL may start simple but it may create confusion later even for expert SQL programmers too. Here, one simple syntax is given below for your reference.
SELECT * FROM Customers;
The syntax seems quite easy and simple. Right? Here, it is asking to select all rows and columns from the customer table. Consider, the customer table has millions of records and each row has a large text field for comments. So, how it will pull down over 10-megabit data every second over the network connection when the row is constrained for an average of 1 kilobyte of data. Perhaps, you must limit the data that can be exchanged over a wire.
For example, you could name a particular row, column, or field that you wanted to extract. You can also filter records for a particular region. In this way, you can make your queries more optimized and they are easy to fetch over a network as well. Also, check out for top 100 clauses like where and order by, etc. that can be clubbed with SELECT query in SQL to optimize the overall database performance.
Every time you are writing a query in SQL, certain rules and regulations should be followed by programmers and developers deeply. There are pre-defined ANSI SQL standards that should be checked by SQL professionals before they start with database programming.
Till the time, we were discussing the SELECT syntax for single tables. What to do when you want to join multiple tables together. Here, we need to join clauses to make things easier for you. For this purpose, you need to understand foreign keys and relationships among tables well. It can be explained by a set of examples in DDL with the help of SQL server syntax. With relational joins, understanding relations in SQL are quite simpler. For every table, there is one primary key constraint that could be taken as the single field or combination of fields defined by the expression. When you want to connect tables then you need foreign keys too along with primary keys. Consider the example as given below:
CREATE TABLE Orders ( OrderID int NOT NULL PRIMARY KEY, ... PersonID int FOREIGN KEY REFERENCES Persons (PersonID) );
The queries can be made longer with the CONSTRAINT keyword where you should give a proper name to the constraint. This is the format that is followed by all database tools. Primary keys are always unique and indexed. At the same time, other fields could be indexed optionally. Further, it is necessary to create indexes for foreign keys too by using the WHERE and ORDER BY clauses.
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Further, there are four types of relational joins – INNER, OUTER, LEFT, or RIGHT, etc. The INNER join is taken by default that considers only rows containing matching values in both tables. If you wanted to list persons whether or not they have an order then you should use LEFT join in that case. If you want to join more than two tables then you can use expressions. Fortunately, there are database development tools that could always help you in designing a robust set of SQL queries just by dragging or dropping commands from the schema diagram to a query diagram.
So, now you know what SQL stands for? In today’s time y, SQL stands for getting popular and accepted widely worldwide. This post takes us back to the Codasyl database space and tells us how SQL came into existence. I hope you must have liked reading this post. TO know more about queries that can be performed on database tables then you should spend more time learning SQL queries from some reputed training provider online. You can also sign up for SQL courses where you will learn more than just what SQL stands for on Janbask Training.
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