SQL Implementation & Administration Querying the Database

Let’s talk BASIC SQL COMMANDS

SQL Commands SQL COMMANDS The basic SQL commands fall into 2 categories: data manipulation language commands (DML) and data definition language commands (DDL). As the names suggest, DML is used to manipulate the data in the database - i.e. to retrieve (query), modify, remove and add data. DDL is used to define database objects. The verbs for the basic SQL commands are: SELECT  - to retrieve (query) data UPDATE - to modify existing data DELETE - to modify existing data INSERT - to add new data We further break down SQL commands into the following categories: Data Creation Data Manipulation Data Retrival Advanced SQL with JOINS, Subqueries and UNIONS

SQL COMMANDS Data Creation SQL Create Database Use this to create a database. -- CREATE DATABASE   database_name Once you create the database, you have to move to it, or select it by using the following command: -- USE   database_name SQL Create Table This SQL Create Table will be used very often throughout the tutorial. It is used to create a table, in our case, mainly to create sample tables. CREATE TABLE table_name    (    field1 data_type [primary key],    field2 data_type [NOT NULL],    field3 data_type [NULL],    . . . .    )

SQL COMMANDS Data Creation SQL Alter Table Used less often, but it is very handy to know this command. With this you can basically edit a table structure. To add a column: ALTER TABLE table_name    ADD new_field data_type [NULL] To delete a column: ALTER TABLE table_name    DROP COLUMN field_name SQL Drop Table Used to delete a table, not just the content. This command is also used very often during the tutorial. So, you need to master this too. --DROP TABLE table_name

SQL COMMANDS Data Retrieval Amongst all SQL Commands, SQL Select can be regarded as the heart and soul of SQL. The main reason for having a database is to retrieve the information. The simplest form of SQL commands is just a SELECT FROM statement. Then if you need to limit the result you introduce the WHERE clause. In the WHERE clause you can use operators such as Like, And, Or, Between, and In. SQL Select Use this to select data from a table or tables. You are able to select all columns in a table or only some columns. You can also select calculated fields or results of another SQL commands. SELECT column_list FROM   Table_name(s)  If you need to select all columns from a table, you can use "*" to replace column_list. SELECT * FROM Table_name(s)

SQL COMMANDS Data Retrieval SQL Distinct Use this to select unique data from a table or tables. SELECT DISTINCT column_list FROM   Table_name(s) The "column_list" after the DISTINCT keyword determine the uniqueness of the rows. If you select only one column, the SQL will select unique entries of that column. If you select two columns, the SQL will select unique combination of those two columns. SQL Where Use this to filter selected results. SELECT column_list FROM   Table_name(s) WHERE  conditions 

SQL COMMANDS Data Retrieval SQL Distinct Use this to select unique data from a table or tables. SELECT DISTINCT column_list FROM   Table_name(s) The "column_list" after the DISTINCT keyword determine the uniqueness of the rows. If you select only one column, the SQL will select unique entries of that column. If you select two columns, the SQL will select unique combination of those two columns. SQL Where Use this to filter selected results. SELECT column_list FROM   Table_name(s) WHERE  conditions 

SQL COMMANDS Data Retrieval SQL Where What you need to know about SQL where are: Enclosed with quotes if the field in where condition is a text field (check with your system, sometimes it allows either single or double quote). If you use numeric field in the condition, use the value only. No quotes around. The equality operators that are allowed for the conditions are: = , > , < , >= , <= or <> (unequal). SQL Like SQL Like is used along with the where clause, as a smart way to search on a pattern. A pattern can include regular characters and wildcard characters. SELECT  * FROM  table_name WHERE  column_name [NOT] LIKE pattern

SQL COMMANDS Data Retrieval SQL Like SQL Like is used along with the where clause, as a smart way to search on a pattern. A pattern can include regular characters and wildcard characters. Wildcards: Wildcard character Description % Match any string, zero or more _ (underscore) Any single character [  ] Any single character within the specified range ([a-f]) or set ([abcdef]). [^] Any single character not within the specified range ([^a-f]) or set ([^abcdef]).

SQL COMMANDS Data Retrieval SQL Count Counting number of rows. -- SELECT count(*) FROM table_name WHERE last_name like ‘%Smith%’ SQL SUM Getting the sum of a field -- SELECT sum(total_cost) from orders SQL MAX This function will return the highest value. -- SELECT max(order_date) from orders SQL MIN This function will return the lowest value. -- SELECT min(order_date) from order SQL AVG This function will return the average value. --SELECT avg(qty) from orders

SQL COMMANDS Data Retrieval SQL ORDER By Sorting the output -- SELECT * FROM table_name(s) ORDER BY COLUMN_NAME SQL AND OR Connecting two or more conditions in the Where or Having clause. --SELECT * from table_name(s) where lastname = ‘Smith’ AND firstname = ‘Frank’ --SELECT * from table_name(s) where (lastname = ‘Smith’ OR lastname = ‘Smyth’) SQL Group By Grouping rows into sets. --SELECT * from table_names GROUP by lastname SQL Having To filter the result of aggregation --SELECT count(*) from orders where lastname = ‘Smith’ Having count(*) > 1 SQL Between Added to conditions to show results between two values. -- SELECT * from Customers where lastname between ‘Smith’ and ‘Turner’

SQL COMMANDS Data Manipulation SQL Update statement is a group of SQL commands to modify data. There are three in this category. SQL Insert command inserts data into a table. SQL Update command updates data in a table. SQL Delete command deletes rows in a table. SQL INSERT To add rows to a table, you use SQL Insert command. There are two methods, one is with the VALUES keyword and second is with a SELECT statement. The syntax to insert a row into a table with values: INSERT INTO table_name[(column_list)] VALUES      (value_list)  The syntax to insert a row into a table from a select statement: The syntax is: INSERT INTO table_name[(column_list)] SELECT column_list FROM  table_name WHERE conditions

SQL COMMANDS Data Manipulation SQL UPDATE To change existing rows, you use SQL Update command. You can use it to change values in a single row, groups of rows or all rows. You can also update a table based on values in other tables. UPDATE table_name SET column_name=expression,column_name=expression, . . . WHERE conditions SQL DELETE To remove rows, you use SQL Delete command. You can delete one rows, group of rows or all rows. You can also delete rows based on values in other tables. DELETE FROM table_name WHERE conditions

Let’s talk INDEXING

SQL Server 2012: Indexing INDEXING One of the most important routes to high performance in a SQL Server database is the index. Indexes speed up the querying process by providing swift access to rows in the data tables, similarly to the way a book’s index helps you find information quickly within that book. The primary reason indexes are built is to provide faster data access to the specific data your query is trying to retrieve. This could be either a clustered or non-clustered index. Without having an index SQL Server would need to read through all of the data in order to find the rows that satisfy the query. If you have ever looked at a query plan the difference would be an Index Seek vs a Table Scan as well as some other operations depending on the data selected. Indexes directly affect the performance of database applications. This article uses analogies to describe how indexes work. The estimated execution plan feature of the Query Window is utilized to compare the performance of two queries in a batch. “An index makes the query fast” is the most basic explanation of an index. An index is a distinct structure in the database that is built using the create index statement. It requires its own disk space and holds a copy of the indexed table data. That means that an index is pure redundancy. Creating an index does not change the table data; it just creates a new data structure that refers to the table. A database index is, after all, is very much like the index at the end of a book: it occupies its own space, it is highly redundant, and it refers to the actual information stored in a different place.

SQL Server 2012: Indexing INDEXING Searching in a database index is like searching in a printed telephone directory. The key concept is that all entries are arranged in a well-defined order. Finding data in an ordered data set is fast and easy because the sort order determines each entries position. A database index is, however, more complex than a printed directory because it undergoes constant change. Updating a printed directory for every change is impossible for the simple reason that there is no space between existing entries to add new ones. A printed directory bypasses this problem by only handling the accumulated updates with the next printing. An SQL database cannot wait that long. It must process insert, delete and update statements immediately, keeping the index order without moving large amounts of data. Indexes are created on columns in tables or views. The index provides a fast way to look up data based on the values within those columns. For example, if you create an index on the primary key and then search for a row of data based on one of the primary key values, SQL Server first finds that value in the index, and then uses the index to quickly locate the entire row of data. Without the index, a table scan would have to be performed in order to locate the row, which can have a significant effect on performance.

SQL Server 2012: Indexing INDEXING In addition to an index being clustered or non-clustered, it can be configured in other ways: Composite index: An index that contains more than one column. In both SQL Server 2005 and 2008, you can include up to 16 columns in an index, as long as the index doesn’t exceed the 900-byte limit. Both clustered and non-clustered indexes can be composite indexes. Unique Index: An index that ensures the uniqueness of each value in the indexed column. If the index is a composite, the uniqueness is enforced across the columns as a whole, not on the individual columns. For example, if you were to create an index on the FirstName and LastName columns in a table, the names together must be unique, but the individual names can be duplicated. A unique index is automatically created when you define a primary key or unique constraint: Primary key: When you define a primary key constraint on one or more columns, SQL Server automatically creates a unique, clustered index if a clustered index does not already exist on the table or view. However, you can override the default behavior and define a unique, non-clustered index on the primary key. Unique: When you define a unique constraint, SQL Server automatically creates a unique, non-clustered index. You can specify that a unique clustered index be created if a clustered index does not already exist on the table. Covering index: A type of index that includes all the columns that are needed to process a particular query. For example, your query might retrieve the FirstName and LastName columns from a table, based on a value in the ContactID column. You can create a covering index that includes all three columns.

Let’s talk INDEXING on VIEWS

Views – Additional Information Creating Indexed Views An indexed view is different from other views because it is materialized and stored on disk in the same way as a table. An interesting point about an indexed view is that the query optimizer may reference a view to improve performance even if it is not referenced in the query. Before you can create an indexed view, you need to make sure that all the referenced tables meet a few requirements. First, all referenced tables must be contained within the same database. If any computed columns in the base tables are not deterministic, they must be removed. Deterministic is defined as always returning the same value or result set. Since a requirement of an indexed view is that it be deterministic, all the columns in the base table must also be deterministic. You can use the following code, which leverages the COLUMNPROPERTY scalar function to determine if the column is deterministic. A clustered index cannot be created on a view if the view references any nondeterministic functions.

Summary SUMMARY As beneficial as indexes can be, they must be designed carefully. Because they can take up significant disk space, you don’t want to implement more indexes than necessary. In addition, indexes are automatically updated when the data rows themselves are updated, which can lead to additional overhead and can affect performance. As a result, index design should take into account a number of considerations.