MySQL Developer Training – Day 5

On day 5, we went through all of the rest of the material in the course. By the end of the day, we had been provided all of the information we should need in order to pass both MySQL Developer examinations. My notes from the final day of class follow.

Day 5

DECLARE statement

  • The declare statement defines items local to a routine
    • Local variables
    • Conditions and handlers
    • Cursors
  • Declare only allowed inside a BEGIN…END
  • Declarations must follow a specific order
    • Variables
    • Conditions – error handler – captures errors that occur in the procedure/function and determines how they should be handled
      • DECLARE condition_name CONDITION FOR condition_value;
      • SQLSTATE Condition value
        • DECLARE null_not_allowed CONDITION FOR SQLSTATE ‘23000’;
        • MySQL errors are strings, so they need to be quoted
      • Continue handler
        • A continue handler allows the procedure to continue even if the condition is met
      • Exit handler
        • An exit handler will stop the procedure/function when the condition is met (an error is generated)
    • Cursors
      • A control structure within stored routines for record retrieval
        • One row at a time
      • A cursor is basically a pointer pointing to the current row we are fetching
      • Cursors are mostly used within loops that fetch and process the rows
      • Asensitive – MySQL decides how to process the information that’s fetched
      • Read-only
      • Non-scrolling
        • The cursor strictly moves from one row to the next
        • You cannot skip records
        • You cannot go backwards
      • Cursors must be declared before declaring handlers
      • OPEN opens a previously declared cursor
      • FETCH
        • obtains the next row using the specified open cursor, and advances the cursor pointer
        • When there is no next row, an error will result
          • You would use that error as a condition to break out of the loop
      • A cursor is destroyed automatically at the end of the BEGIN…END block
      • If you choose to close the cursor ahead of time, you can use the CLOSE command
      • Prepared statements can only have one cursor, and it is not named
    • Handlers


  • Named database objects
  • Activated when

Creating triggers

  • CREATE TRIGGER trigger_name { BEFORE | AFTER }
    ON table_name
    INSERT INTO DeletedCity (ID, Name) VALUES (OLD.ID, OLD.Name);
  • OLD and NEW are keywords that can be used within triggers

Trigger error handling

MySQL handles errors during trigger execution as follows:

  • Failed BEFORE triggers
    • Operation on corresponding row is not performed
  • After trigger execution
    • BEFORE trigger events and the row operation will execute successfully in non-transactional tables
    • In transactional tables, a rollback of all changes made by the statement will occur

Disallowed statements

  • SQL prepared statements
  • Explicit or implicit COMMIT or ROLLBACK
  • Return a result set
  • Recursive – cannot modify a table that is in use (reading or writing)
    • These types of things must be taken care of in BEFORE statements, rather than AFTER statements, because the table will not yet be open at that point

Storage Engines

SQL Parser and storage engines

  • Client sends requests to the server as SQL
  • Two-tier processing
    • Upper tier includes SQL parser and optimizer
    • Lower tier comprises a set of storage engines
  • SQL itself is not engine-specific, generally
    • Some exceptions include COMMIT, ROLLBACK, CREATE TABLE (which needs an engine declaration and can allow foreign key information for transactional tables), etc.
  • Steps to parse and return
    • Parse
    • Optimize
    • Retrieve/Store
      • This is where things like ORDER BY, GROUP BY, etc. are performed
  • Storage medium
  • Transactional capabilities
    • InnoDB allows transactions while MyISAM does not
  • Locking
    • InnoDB locks on a row-by-row basis
    • MyISAM locks on a table-by-table basis
  • Backup and recovery
    • MyISAM allows you to physically copy individual tables, etc. from one place in your filesystem to another place
    • InnoDB stores its information for all databases on the server in a single file, so it is more difficult to copy individual items
  • Optimization
  • Special features
  • MySQL server operates same for all storage engines
    • SQL commands independent of engine

Available Storage Engines

  • MySQL provides and maintains several storage engines
  • Also compatible with many third party engines
  • MySQL developed:
    • MyISAM
      • Incredibly fast – even more so when you use compression, fixed-width columns and good indexing
      • Data stored in table
      • Table-level locking
      • Does not support transactions
    • Falcon
    • NDB/Cluster
    • Memory
      • Data is in memory
      • Fastest engine that exists, but nothing is stored anywhere on disk
    • Archive
      • Highly compressed
      • Only supports INSERT and queries
    • Federated
      • creates an alias of an existing database on a separate server
    • Blackhole
    • CSV
    • Example – doesn’t do anything, but is in the code to show people a template of how to create an engine
  • Third party engines
    • InnoDB
      • Transactional
      • Foreign key constraints
      • Row-level locking
      • Backups
    • solidDB
    • InfoBright BrightHouse
    • Nitro
    • PBXT

You can set the storage engine when creating a table, but you are not required to do so. If you do not specify the engine, it will be set to the database default

MyISAM Storage Engine

  • MyISAM is the MySQL default
  • Manages tables with specific characteristics
    • Represented by three files
    • Most flexible AUTO_INCREMENT
    • Fast, compressed, read-only tables save space
    • Manages contention between queries
      • By default, writing to disk takes precedence over reading from disk, but that can be overridden
      • SELECT statements can be set to a higher priority with the HIGH PRIORITY switch
      • UPDATE, DELETE and INSERT statements can be set to a lower priority with LOW PRIORITY
      • INSERT statements can also be set to an extremely low priority with DELAYED
    • Portable storage format
    • Specify number rows for a table
    • Disable updating of non-unique indexes and enable the indexes
      • Indexes of non-unique keys can be disabled so that the indexes are not re-created each time a row is changed. The indexes will be rebuilt when the keys are reenabled
    • Tables take up very little space
  • Three row storage formats
    • Fixed-row format
    • Dynamic row format
    • Compressed format
      • Tables must be deliberately compressed
      • Compressed tables are read-only
        • Tables must be decompressed to modify
      • Using the myisampack utility
        • Includes a mixture of “True” compression and a set of optimizations
        • Each record compressed separately with small cost to decompress
        • Must be performed on the host machine
      • Use myisamchk afterward to update the indexes
      • Always backup tables prior to running utilities
  • Table-level locking
  • Acquiring locks
  • Tables with no holes support concurrent inserts
    • If a table is completely defragmented, any number of inserts can all be performed at the same time
  • Tables with holes do not support concurrent inserts by default
  • Can change priority of statements that retrieve or modify data
  • Write request not processed until current readers finished

InnoDB Storage Engine

  • Manages tables with specific characteristics
    • Represented on disk by a .frm format file as well as data and index storage
    • Supports transactions
    • ACID compliant
      • Satisfies ACID conditions
      • General locking properties
        • Does not need to set locks to achieve consistent reads
        • Uses row-level locking per concurrency properties
        • May acquire row locks as necessary to improve concurrency
        • Deadlock is possible
      • Supports two locking modifiers
      • Repeatable Read isolation level allows modifiers
    • Auto-recovery after crash
    • MVCC and non-locking reads
    • Supports foreign keys and referential integrity
    • Supports consistent and online logical backup
  • Tablespace for storing all table contents together
  • Log files for recording transaction activity
  • Format file (.frm)
  • Logical storage area can contain multiple files
  • Table-specific file (.ibd)
    • –innodb-file-per-table
  • Manages InnoDB-specific log files
  • Log files used for auto-recovery

Memory Engine

  • Uses tables stored in memory
    • Tables are temporary
  • Must have fixed-length rows
  • Manages tables with specific characteristics
  • Formerly HEAP engine
  • Memory indexing options
    • Uses HASH indexes by default
    • BTREE is preferable for some operators
      • Ranges


  • Server processes queries more efficiently and performs better
  • Optimization strategies
    • Use indexing properly
      • Large tables require indexing for efficiency
      • Benefits of indexes
        • Contain sorted values
        • Use less disk I/O
        • Enforce uniqueness constraints
      • Downsides of indexing
        • Any time anything in the table is changed, the indexes have to be rebuilt
        • Can slow down some data manipulations
        • Uses additional space
      • Types of indexes
        • Three general types
          • Primary key
          • Unique
            • Allows NULLs, but other than that requires the value of the cell to be different than anything else in the column
          • Non-unique
            • Allows NULLs and allows duplicate entries
      • Primary versus unique
        • Primary cannot contain NULL
        • Only one primary key is allowed per table
      • Adding indexes
        • ALTER TABLE table_name ADD PRIMARY KEY(column_name);
        • CREATE INDEX index_name ON table_name(column_name);
      • Removing indexes
        • ALTER TABLE table_name DROP PRIMARY KEY;
        • ALTER TABLE table_name DROP INDEX index_name;
        • DROP INDEX index_name ON table_name;
        • DROP INDEX `PRIMARY` ON table_name;
          • PRIMARY must be contained within back tick quotes, because it is a name. If it is not within back ticks, it will be treated as a keyword that doesn’t belong in that syntax
          • PRIMARY is the official name of the primary key in a table
      • Using index prefixes
        • Several column types
        • Use only specified, leading part of column values
        • Can make the index work faster, because it only searches a specific portion of the column value
        • CREATE INDEX part_of_name ON customer (name(10));
        • Can be used on composite indexes, as well
          • INDEX (column_name1(15),column_name2(10))
      • You can show index information by using the SHOW INDEX command
        • Full text indexes
          • Only useful with MyISAM tables
          • Definition can be given with CREATE TABLE, ALTER TABLE, CREATE INDEX
          • Create index after table creation for large datasets
          • Use MATCH()…AGAINST() syntxt
          • SELECT title FROM books WHERE MATCH(title) AGAINST (‘prince potter’)
    • Well-written queries
      • Using EXPLAIN to determine query processing
      • Returns useful information
        • Shows if index is required
        • Shows if index is being used
        • Analyzes query rewrites
      • EXPLAIN works with SELECT queries
      • EXPLAIN for JOINs
        • Joins tend to increase amount of server processing
        • EXPLAIN can help reduce server impact
        • The type column indicates the join type
        • type column output
          • system
          • const
          • eq_ref
          • ref
          • ref_or_null
          • index_merge
          • unique_subquery
          • index_subquery
          • range
          • index
          • ALL
      • The extra column (page 21-22)
        • using index
        • where used
        • distinct
        • not exists
      • Inefficient query “extra” output
        • using filesort
        • using temporary
        • range checked for each record
      • Indicators of worst performance
        • using filesort
        • using temporary
      • Rewrite query and run EXPLAIN again
      • Efficiency principles
        • No indexed columns within an expression
        • Beneficial for joins that compare columns from two tables
        • Use same value as column data type
          • WHERE id=18 (if column is a number)
          • WHERE id=’18’ (if column includes strings)
        • Pattern matching
          • WHERE name LIKE ‘de%’
          • WHERE name >= ‘de’ AND name < ‘df’ – not as good as example above
          • WHERE name LIKE ‘%de’ – full table scan
        • Rewrite using a trigger that maintains an additional column
          • WHERE LENGTH(column)=5 – bad
          • WHERE column_length=5 – column_length is a separate column that’s been automatically generated to show the value that would be returned by LENGTH(column)
        • Reduce amount of output a query produces
          • Use the LIMIT clause
            • Reduces information going over the network
            • Allows server to terminate query processing earlier
          • Use the WHERE clause
          • More improvement with index or column
      • Techniques for updating tables
        • Use DELETE and UPDATE same as SELECT
        • Multi-row INSERT
        • INSERT INTO t (id, name) VALUES (1,’Bea’),(2,’Belle’),(3,’Bernice’);
        • Better performance with a transaction
        • LOAD DATA INFILE faster than multi-row INSERT
          • Even faster with MyISAM if you disable keys before running the file and enabling them when finished
        • Use REPLACE rather than DELETE plus INSERT
    • Generating summary tables
      • Select records to generate summaries
      • Summary table strategy
      • Several benefits to this strategy
      • Table-locking table will be available more
        • The use of the temporary table will not affect the original table from which it was derived
      • Consider making a memory table
      • CREATE TABLE ContinentGNP
        SELECT Continent, AVG(GNP) AS AvgGnp
        FROM Country GROUP BY Continent
      • Disadvantages
        • Values are only good until changed
        • Storing data twice
    • Choose best matching storage engine
      • Decide query types during table creation
      • Choose storage engine with locking level needed
      • InnoDB good for a mix of retrievals and updates
      • MyISAM table structure dependent on the higher priority between speed or disk
        • Choose fixed-length or variable-length according to needs
        • Use read-only tables if possible
      • CHAR columns take more space than VARCHAR
        • considerably faster in MyISAM, but CHAR is no different (in speed) than VARCHAR in InnoDB
      • Use Memory for temporary information

* Within a MyISAM table, you can temporarily disable all non-unique keys so that new indexes will not be built while they are turned off. Use the statement ALTER TABLE table_name DISABLE KEYS. You can turn them back on with ALTER TABLE table_name ENABLE KEYS.

MySQL Developer Training – Day 4

On day 4, we continued where we had left off on day 3. We covered subqueries, views, prepared statements, importing and exporting data, stored routines and some of the basic functions that are available within stored routines. My notes from day 4 follow.

Day 4


Subqueries are the reason behind the name “structured query language,” as subqueries are “structured queries”.

  • A subquery is a query nested inside another query
  • Enclosed inside parentheses in order to specify that the subquery should be completed first
  • SELECT Language
    FROM CountryLanguage
    WHERE CountryCode = (
    SELECT Code
    FROM Country
    WHERE Name=’Finland’);

Why use a subquery?

Result Table Types:

  • Scalar – Single row with a single column
  • Row – Single row with one or more columns
  • Column – Single column with one or more rows
  • Table – One or more rows with one or more columns
  • Empty – No row or column data

Correlated and non-correlated

  • Correlated
    • References outer query
    • Cannot stand alone
    • Tend to be inefficient from a time standpoint, as the engine has to go back and forth between the inner and outer query
    • Tend to be more RAM efficient than JOINs, because it does not have to store a separate memory table from which to pull the final results
    • SELECT Country.Name
      (SELECT COUNT(*) FROM City
      WHERE CountryCode=Country.Code)
      AS CityCount FROM Country;
  • Non-correlated
    • Does not reference outer query
    • Can stand alone
    • Ideally, a non-correlated subequery would only be read once
    • SELECT Name FROM City WHERE CountryCode IN
      (SELECT Code FROM Country
      WHERE Continent=’Oceania’);

Subquery placement

  • If you place a subquery in the “column” portion of the query, then you can return and use only a scalar result
    • SELECT name,
      (SELECT MAX(Population) FROM City
      WHERE City.CountryCode = Country.Code)
      AS LargestCity
      FROM Country LIMIT 8;
  • Inside the FROM clause, you could return and use a table result, which can also include column, row and scalar results
    • Every column must have a name
    • Subquery can be a table query
      • Even if all values are not used
    • The following example is not something we could return with a JOIN
      • SELECT AVG(cont_sum)
        FROM (SELECT Continent, SUM(Population) AS ContinentSum
        FROM Country
        GROUP BY Continent)
        AS t;
    • Any time you have a subquery in a FROM clause, you must alias the created table, even if you don’t use that alias name anywhere else in the query
  • In the WHERE clause, when using an “equals” comparison, you can return and use scalar or row results
    • In order to use row results, you would have to use a tupple
      • (SELECT x, y FROM mytable WHERE key = 5) = (value, value)
      • (x, y) = (z, a)
        • Either or both sides of the tupple equation can be subqueries, themselves
    • Compares outer query with subquery results to see if they are the same
    • SELECT Continent, Name, Population
      FROM Country c
      WHERE Population = (SELECT MAX(Population)
      FROM Country c2
      WHERE c.Continent = c2.Continent
      AND Population > 0

      • In the example above, you do not need the “> 0”, because simply stating the name of the column will evaluate as 0 or 1 (false or true)
  • In the WHERE clause, when using greater than or less than comparisons, you can only use and return a scalar result
    • SELECT
  • In the WHERE clause, when using IN, ALL, ANY, SOME, etc., you can use and return a table result (or any other type of result)
    • In order to use a table result, you would need to use a tupple
      • Using a tupple would look something like:
        WHERE CountryCode, Name, Population IN (SELECT Code, Name, Population FROM Country…)
      • A tupple will compare from left to right, matching the columns in the left list up with the columns in the results returned by the right set
    • SELECT Name, Population FROM City
      WHERE CountryCode IN(
      SELECT Code FROM Country
      WHERE Continent = ‘Europe’)
      ORDER BY Name LIMIT 10;
    • SELECT Name FROM City
      WHERE Population >
      ALL (SELECT Population FROM City
      WHERE CountryCode = ‘CHN’);

      • The example above will compare each result returned against all of the results returned in the subquery. If any of the results in the subquery do not match the criteria, the whole result will return false
      • The specific example above could have been optimized to read something like:
        • SELECT Name FROM City WHERE Population > (SELECT MAX(Population) FROM City WHERE CountryCode = ‘CHN’);
    • SELECT Name
      FROM Country
      WHERE Continent = ‘Europe’
      AND Code = ANY(SELECT CountryCode
      FROM CountryLanguage
      WHERE Language=’Spanish’)
      ORDER BY Name;
  • In the WHERE clause, when using EXISTS, you can only return an empty result set (you are simply checking to see if you get any results or not, you are not using any information from the query itself
    • In current versions of MySQL, this type of result is not optimized – MySQL will complete the subquery before returning 0 or 1 (true or false)
    • In future versions, this type of result should be optimized, so that the engine will stop the subquery as soon as a result is returned, and will then return a 1
    • SELECT Continent FROM Country WHERE EXISTS
      (SELECT * FROM City WHERE Code = CountryCode AND Population > 8000000)
      GROUP BY Continent;

      • Will return a list of each continent that contains at least one country with a population over 8000000
    • SELECT Continent FROM Country WHERE NOT EXISTS
      (SELECT * FROM City WHERE Code = CountryCode AND Population > 8000000)
      GROUP BY Continent;

      • Is not the opposite of the query above
      • Will return a list of each continent that contains at least one country with a population under 8000000

Other Subquery Uses

Using Subqueries in UPDATE and DELETE statements

You can use subqueries to locate rows on which you want to perform updates or you want to delete

  • Subqueries are not limited to SELECT statements
  • They can be used in DELETE and UPDATE statements
    • DELETE FROM City WHERE CountryCode IN (
      SELECT Code FROM Country WHERE LifeExpectancy < 70.0);
  • Generally, when dealing with DELETE and UPDATE statements, the subquery is used within the WHERE clause

Converting subqueries to JOINs

  • Joins can be more efficient than subqueries
    • Convert a subquery to a join if the subquery is running slowly
  • Subquery versus JOIN
    • Subquery:
      • SELECT Name FROM Country
        WHERE Code IN (
        SELECT CountryCode FROM CountryLanguage);
    • JOIN:
      • SELECT DISTINCT Name FROM Country
        JOIN CountryLanguage ON Code=CountryCode;


  • Database object defined in terms of a SELECT statement
    • SELECT statement masquerading as a table
    • Will stay in the database until it is destroyed
  • Selected from base tables or views
  • Updatable
  • Views are nestable

CREATE VIEW statement

  • Define a view
  • General syntax:
    • CREATE VIEW view_name AS select_statement
      • CREATE VIEW CityView AS SELECT ID, Name FROM City;
  • Optional parts of a CREATE VIEW statement
      • Will replace an existing view of the same name if it exists, will create a new view if not
      • MERGE
      • TEMPTABLE (TempTable)
        • Will create a temporary table if the view is too large to fit into RAM
    • DEFINER = { user | CURRENT_USER }
      • The definer, by default, is the person who created the view
    • column_list
      • By default, if the column_list is not specified, the names of the columns in the original table will be used as the column names in the view
      • You can optionally define new column names for each of those
      • CREATE VIEW v
        AS SELECT Country.Name AS CountryName, City.Name AS CityName
        FROM Country, City WHERE CountryCode=Code;
    • WITH CHECK OPTION (see insertable views below)
      • Places constraints on allowable modifications
      • Checks the WHERE conditions for updates
        • If the update or insert statement would result in something that would not be visible in the view, then the CHECK OPTION will stop the statement from being executed successfully
      • Example:
        • CREATE VIEW LargePop AS
          SELECT Name, Population FROM Country
          WHERE Population >= 100000000
        • SELECT * FROM LargePop;
        • UPDATE LargePop SET Population = Population + 1 WHERE Name=’Nigeria’

It is possible to update a table through a view

  • Can use UPDATE and DELETE
    • Updating and deleting information from a view will update or delete that information inside of the base table on which the view is based.
    • Information in the view does not actually exist in the view – it only exists inside the base table(s) on which the view is based
  • Must be one-to-one relationship
  • Updatability examples
    • CREATE VIEW EuropePop AS
      SELECT Name, Population FROM Country
      WHERE Continent = ‘Europe’;
    • UPDATE EuropePop SET Population = Population + 1 WHERE Name = ‘San Marino’;

Insertable Views

  • An updateable view can be insertable
    • Must meet additional requirements
    • No duplicate view column names
    • Must contain all columns from base table without default value
    • Cannot be derived columns (calculated, etc.)
  • Inserting views with AUTO_INCREMENT
    • LAST_INSERT_ID() will not work if the AUTO_INCREMENT column is not visible through the view

Checking Views

  • When you define a view, the object referenced must exist
  • A view can become invalid if a referenced object is removed
  • Using CHECK TABLE will show that the view is no longer valid

Altering Views

  • You can use ALTER VIEW to change an existing view
  • Is basically the same as CREATE OR REPLACE


  • Views table in database
    WHERE TABLE_NAME = ‘CityView’
    AND TABLE_SCHEMA = ‘world’\G

SHOW statements

  • Display Metadata
  • SHOW CREATE VIEW specifically for views

Prepared statements

  • Useful for running multiple similar queries
  • Can use same structure and change data values
  • Enhanced performance
    • Statement parsed only once by server
    • May require fewer conversions
    • Less traffic between server and client

Prepared statements from MySQL

  • Aids in testing and debugging
  • Session-bound
    • Prepared statements are tied to sessions and will be automatically destroyed when the session is closed
  • User defined variables pass values from one statement to another
    • Connection specific
    • Also known as @ variables
      • variables stay in RAM until the connection is closed
      • variables will not persist across connections
    • Use SET statement to define
    • Example syntax
      • SET @var_name = expr [, @var_name = expr]…
      • SET @myvar = 12, @myothervar = 5*2
    • Expression can evaluate to an integer, real, string or NULL
    • Coercibility is implicit
      • Uses the type of the string that we supply
      • If we do not supply a type, it will inherit the charset and collation of the connection
  • PREPARE my_stmt FROM
    ‘SELECT COUNT(*) FROM CountryLanguage WHERE CountryCode = ?’;
  • SET @code = ‘ESP’; EXECUTE my_stmt USING @code;
  • Using variables inside the prepared statement
    • You can have more than one question mark inside the prepared statement
    • They will be parsed in the order in which they appear within the statement
      • To supply multiple variables to be assigned to the multiple unknowns, you would separate the variable names with commas in the execute statement
  • If you want to destroy the prepared statement before closing the connection
    • DROP PREPARE my_stmt;
    • You do not have to use an unknown (question mark) inside a prepared statement

Preparing a statement

PREPARE namepop FROM ‘

SELECT Name, Population
FROM Country
WHERE Code = ?


  • Not all SQL statements can be prepared
  • Limited to the following
    • SELECT
    • Data modification: INSERT, REPLACE, UPDATE, DELETE
    • SET, DO and many SHOW statements
    • CREATE TABLE statements
  • As of MySQL 5.1, many more features were added

Exporting and Importing Data

Import Data using SQL


  • Imports data into a table from a file
  • Uses similar clauses and format specifiers as SELECT…INTO OUTFILE
  • MySQL assumes file is located on server host
    • In database data directory
  • Tab delimited or comma separated files
  • Characteristics to know about input file
  • CSV example:
    • LOAD DATA INFILE ‘C:/City.txt’ INTO TABLE City
      ENCLOSED BY ‘”‘
  • Specifying data file location as client host
    • You have to have the proper security permissions in order to do this
  • Skipping or transforming column values
    • LOAD DATA INFILE ‘C:/City.txt’ INTO TABLE City
  • Duplicate records
    • Can control duplicate records with IGNORE and REPLACE
    • Behavior differs slightly
    • IGNORE and REPLACE are mutually exclusive
      • REPLACE will delete the original record and create a new one with the new information if it finds a duplicated key
      • IGNORE will skip the new record if its key already exists in the table
  • To alter the structure of the data in order to make it fit into your table properly
    • LOAD DATA INFILE ‘C:/people.txt’ INTO TABLE People
      ENCLOSED BY ‘”‘
      (@skip, @firstname, @lastname, @date, address, email, …)

      • The items enclosed in parentheses above are in the order in which they appear within the data file that I’m loading
      • The items not preceded by @ symbols are the names of the columns in my table
      • The variable @skip in the example above is an undefined variable, which, by default, is equal to NULL
        • In this example, we are simply using that variable name to specify a column that does not need to be inserted into our table
    • SET Name = CONCAT(@lastname,’, ‘,@lastname),
      Birthdate = str_to_date(@date,’%b %e %Y’);

      • The date in the example above would have been in the format of Sep 6 2001

Export Data using SQL


  • Writes result set directly into a file
  • MySQL assumes filepath to be in database data directory, unless otherwise specified
    • Path is relative to the host machine on which the SQL server is running
  • SELECT * INTO OUTFILE ‘C:/City.txt’ FROM City;
  • INTO OUTFILE Changes SELECT Operation
    • File written to server host, instead of over the network to client
    • If the file already exists, this command will generate an error rather than overwriting or appending
  • Specifiers
    • Default is tab delimited with newline terminators
    • Can change specifiers for all columns
      • FIELDS TERMINATED BY ‘string’
        • defines data values within a line
      • ENCLOSED BY ‘char’
      • ESCAPED BY ‘char’
      • LINES TERMINATED BY ‘string’
    • Terminator definitions
      • \N – NULL
      • \O – NUL (zero) byte
      • \b – backspace
    • Line terminator specifiers
      • Newline character is the default
    • CSV format text file example
      • SELECT * INTO OUTFILE ‘C:/City.csv’
        ENCLOSED BY ‘”‘
        FROM City;

Export using the mysqldump database backup client

  • MySQL utility to export (dump) table contents
    • Full structure
    • Data only
    • Table structure only
    • In standard format
    • MySQL specifics for optimized speed
    • Compressed
  • Three ways to invoke mysqldump
    • mysqldump [options] db_name [tables]
    • mysqldump [options] –databases db_name1 [db_name2 db_name3…]
    • mysqldump [options] –all-databases
  • Can only be executed from the shell
  • Need to redirect the output into a file, otherwise it just prints the dump onto the screen
    • mysqldump -uroot -p<password> world >C:/world_dump.sql
  • File contains commands needed to recreate tables and data
  • Export to a specific table in a database
    • mysqldump -uroot -p<password> world CountryLanguage

Import using the mysqlimport client

  • MySQL utility to load data files into tables
  • Command line interface to LOAD DATA INFILE
  • mysqlimport options db_name input_file
  • Can only be executed from the shell
  • The table the information is being imported into must have the same name as the file you are loading from
  • Options
    • –help
    • –lines-terminated-by=string
    • –fields-terminated by=string…

Import data with the source command

  • Import table data
    • mysql -u root world < CountryLanguage.sql
    • Path is relative to the local machine
  • Loading the data
    • SOURCE C:/CountryLanguage.sql
    • Source uses a path relative to the client machine (your machine, not the server)
  • The default is to not write over existing databases, unless specified inside the script file that you’re loading

Stored Routines

What is a stored routine?

  • Set of SQL statements that can be stored in server
  • Types
    • Stored procedures
      • A procedure is invoked using a CALL statement, and can only pass back values using output variables
      • Procedures are database-specific
    • Stored functions
      • A function can be called from inside a statement and can only return a scalar value
      • Are invoked like a normal function
  • We use stored routines for the following reasons
    • Performance
    • Security
      • Minimal data access
      • Single location processing
    • Client applications
      • One application
      • One programming language
        • Instead of trying to translate your functions, etc. into each of the different languages you’re using to access the data, you can simply write it in MySQL as a stored routine
    • Function libraries
  • Stored routine issues
    • Increased server load
      • Because MySQL is doing all of the work, none of it is being passed off to other sources
    • Limited development tools
      • You can only use MySQL commands within your stored routines
    • Limited functionality and speed
      • There is no way to compile routines, etc.
    • No debugging/profiling capabilities
      • You can trace by downloading a specific version of the source and compiling it yourself, but that is not recommended

Creating Stored Routines

Create procedure

  • CREATE PROCEDURE procedure_name() procedure_statement
    • Single statement example:
    • CREATE PROCEDURE world_record_count ()
      SELECT ‘country count ‘,COUNT(*) FROM Country;

Create function

  • CREATE FUNCTION function_name() RETURNS return_type function_statement
    • Single parameter example
      • CREATE FUNCTION ThankYou(s CHAR(20)) RETURNS CHAR(50) RETURN CONCAT(‘Thank You, ‘,s,’!’);

Compound statements

  • Delimiter and BEGIN…END
    • DELIMITER // – sets the alias of the go command as “//”
      CREATE PROCEDURE world_record_count() – creates the procedure
      BEGIN – opens our list of commands
      SELECT ‘country count ‘, COUNT(*) FROM Country; – a statement that will be run
      SELECT ‘city count ‘, COUNT(*) FROM City; – another statement
      SELECT ‘countrylanguage count’, COUNT(*) FROM countrylanguage; – another statement
      END// – ends our list of commands and then tells the server to execute
      DELIMITER ; – sets the delimiter back to a semi-colon

Assign Variables

    • Declaring
    • Scope
      • Variables declared within a function definition are only valid within that function defnition
    • DELIMITER //
      CREATE FUNCTION add_tax (total_charge FLOAT(9,2)
      RETURNS FLOAT(10,2)
      DECALRE tax_rate FLOAT(3,2) DEFAULT 0.07;
      RETURN total_charge + total_charge * tax_rate;
      RETURN Fbill;
      END //
    • Global variables
      • SELECT SUM(population) FROM country INTO @worldpop;
        …is equivalent to…
        SELECT SUM(population) INTO @WorldPop FROM country;
      • SELECT SUM(population), AVG(population) FROM Country INTO @worldpop, @worldavg;
    • Local Variables
      • SELECT COUNT(*) FROM city INTO Total_Cities;
        …is equivalent to…
        SELECT COUNT(*) INTO Total_Cities FROM City;
  • SET
    • The SET statement allows the user to assign a value to a user defined variable using either = or := as the assignment operator

Variable Scope

  • Local Variable
  • Routine parameter
  • Local variable in an inner block
  • Local variable in an outer block
    CREATE PROCEDURE precedence(opal INT)
    SELECT opal FROM test_table;
    SELECT opal FROM test_table;
  • Variables must be defined immediately after the BEGIN statement in the block

Parameter declarations

  • Stored procedures
    • IN (Default)
      • Indicates an input parameter which is passed in from the caller to the procedure
    • OUT
      • Indicates an output parameter which is set by the procedure and passed to the caller after the procedure terminates
      • NULLs the variable when it’s passed to the function
      • Can be used to set a “success/failure” flag
    • INOUT
      • Indicates a parameter that can act as an IN and an OUT parameter
    • OUT and INOUT variables will be passed ByRef (meaning that anything that happens to the variable inside of the procedure will happen to the original variable)
  • Stored functions
    • For stored functions, only IN is available

Execute Stored Routines

  • Executing procedures
  • Executing functions
  • Implications of database association
    • You need to declare the appropriate database in which the routine is stored
    • If the database is deleted, the routine is deleted, too

Alterable stored routine characteristics

      • DEFINER
      • INVOKER
    • Data use (SQL)
      • NO SQL

Non-alterable stored routine characteristics

  • Non-alterable
      • The routine always produces the same result when invoked with a given set of input parameter values
    • NOT DETERMINISTIC (default)
      • The routines results can possibly change when invoked with a given set of input parameter values
      • Provides the parser with the programming language to use when parsing the stored routine created
      • This cannot change because MySQL is the only language available

Examine Stored Routines


Delete Stored Routines

DROP PROCEDURE [IF EXISTS] procedure_name;
DROP FUNCTION [IF EXISTS] function_name;

Flow control statements

  • Statements and constructs that control order of operation execution
  • Common flow controls
    • Choices
      • IF
        • IF(test condition) THEN

          ELSEIF(test condition) THEN


          END IF;
        • ELSEIF needs to be all one word
      • CASE
        • CASE provides a means of developing complex conditional constructs
        • CASE works on the principle of comparing a given value with specified constants and acting upon the first constant that is matched
        • CASE case_value
          WHERE when_value THEN


          END CASE;
        • CASE
          WHEN test_condtion THEN


          END CASE
        • If none of the cases are met and there is no “else” specified, it will throw an error
        • In the first example, it is strictly a binary comparison, meaning that case-sensitivity is a factor
    • Loops
      • REPEAT
        • The repeat statement repeats and SQL statement until the search condition that is set becomes true
        • A repeat statement is always run at least once
        • Labels: Begin and End
        • begin_label: REPEAT

          UNTIL test_condition
          END REPEAT end_label;
      • WHILE
        • WHILE repeats an SQL statement while a set condition is true
        • The statement list can consist of one or more statements
        • begin_label: WHILE test_condition DO

          END WHILE end_label;
      • LOOP
        • The statements within the loop are repeated until the loop is exited; usually this is accomplished with a LEAVE statement
        • begin_label: LOOP

          LEAVE label;
          END IF
          END LOOP end_label;
  • Other Label Flow Control Constructs
    • LEAVE
      • This statement is used to exit any labeled flow control construct within a LOOP, REPEAT or WHILE statement
      • LEAVE can also be used in Labeled BEGIN…END compound statements
      • This statement simply means “do the LOOP (or REPEAT or WHILE) again”