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Put MySQL in PATH

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After downloading and installing MySQL 8.0.24 yesterday, I opened a command shell. In the command shell, I could access the MySQL Shell (mysqlsh.exe) but not the MySQL Client (mysql.exe). Typing in the following:

C:\WINDOWS\system32>mysql

It returned:

'mysql' is not recognized as an internal or external command,
operable program or batch file.

The MySQL Client (mysql.exe) was installed because MySQL Workbench relies on it. However, the MySQL Microsoft Software Installer (MSI) does not put the mysql.exe file’s directory in the common Windows %PATH% environment variable. You can find the required %PATH% directory variable by opening the File Manager and searching for the mysql.exe file.

You should return several directories and programs but the directory you want is:

C:\Program Files\MySQL\MySQL Server 8.0\bin

You can test it by using the SET command in the Microsoft Operating System, like this:

SET PATH=C:\Program Files\MySQL\MySQL Server 8.0\bin;%PATH%

You can now call the mysql.exe program in your current shell session with the following syntax:

mysql -uroot -p

You will be prompted for the password and then connected to the database as follows:

Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 19
Server version: 8.0.24 MySQL Community Server - GPL
 
Copyright (c) 2000, 2021, Oracle and/or its affiliates.
 
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
 
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
 
mysql>

Unfortunately, the SET command only sets the %PATH% environment variable in the current session. You can set the system %PATH% environment variable globally by following these steps:

  1. In Search, search for and then select: System (Control Panel)
  2. In Settings dialog enter “Environment” in the search box and it will display:


  3. Chose “Edit the system environment variables” option. You will see the following “System Properties” dialog:

  4. Click the “Environment Variable” button to display the “Environment Variables” dialog. Click on the Path system variable before clicking the Edit button beneath.

  5. Click the “New” button and enter “C:\Program Files\MySQL\MySQL Server 8.0\bin, and click the “OK” button. The next time you query the computer system’s %PATH% environment variable, it will show you the list of path locations that the operating system looks at for command files. It’s actually stored as a semicolon-delimited list in Windows 10 (and, as a colon-delimited list in Linux or Unix).

    6. The next time you open a command shell, the %PATH% environment variable will find the mysql.exe program. As always, I hope these instructions help the reader.

Written by maclochlainn

April 23rd, 2021 at 12:51 am

Posted in MySQL,MySQL 8,MySQL Workbench,Uncategorized,Windows 10

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MySQL Script Test

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There are many ways to test and edit files. A lot of developers only use their favorite Integrated Developer Environment (IDE) but I find testing script files within the scope of a pipelined set of scripts much faster.

The ability to edit a script from within the MySQL Command-Line Interface (CLI) or MySQL Shell would be nice but unfortunately, doesn’t exist. You can always subshell to edit a file or list files in the present working directory, like:

mysql> \! vi task.sql

I prefer to test at the OS level while leveraging the up-arrow key for command history. Here’s my quick edit and test script technique from your present working directory:

  1. Assume you create a task.sql test file, like: 

    SELECT user() AS "Current User"\G
  2. You can edit with vi or emac and test the script interactively from the present working directory.

    • You can edit the file with the following syntax: 

      vi task.sql
    • then, you can test the task.sql file:

      mysql -ustudent -p -Dstudentdb < task.sql
    • It returns the following: 

      Enter password: 
*************************** 1. row ***************************
Current User: student@localhost
    • If you have the desired outcome, you’re done. However, if you need further change you repeat the process.

As always, I hope this helps those looking for a quick way to accomplish a task.

Written by maclochlainn

April 11th, 2021 at 1:09 pm

Posted in Linux,MySQL,MySQL 8,MySQL Client

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MySQL & macOS Silicon

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It’s a problem for my students who purchased the new Apple hardware that uses Apple Silicon because they can’t install a Docker MySQL instance. However, there is Homebrew formula that works on macOS Big Sur and the new Apple silicon. It supports:

  • Intel Silicon: macOS Big Sur, Catalina, and Mojave
  • Apple Silicon: macOS Big Sur

The Homebrew Formula does have conflicts that you may need to avoid. It is a solution for those with the new Apple silicon.

As always, I hope this helps those looking for a solution.

Written by maclochlainn

April 3rd, 2021 at 10:15 am

Posted in Apple,macOS,MySQL,MySQL 8

Tagged with , ,

MySQL Transaction Scope

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The idea of ACID transactions are a basic feature of SQL’s individual Data Manipulation Language (DML) commands, like the INSERT, UPDATE, and DELETE statements. Transactions across two or more tables are a natural extension of ACID compliance features provided by DML commands. However, they require a structured programming approach, like a store procedure or like API implemented in an imperative language.

Surprisingly, transaction management wasn’t covered well in Alan Beaulieu’s Learning SQL because he only provided pseudo code logic. While I thought troubleshoot some broken MySQL SQL/PSM logic would be a good learning experience for students, it wasn’t. So, I wrote this sample code to show how to achieve an all or nothing transaction across four tables.

The code for this example on transaction management lets you perform the important tasks necessary to effect transaction management:

  • You must disable autocommit in the scope of the session.
  • You must use an imperative programming language like SQL/PSM or Python, et cetera.
  • You must identify an error thrown in a series of DML transactions, rollback all completed work, and exit the scope of the program unit.

This SQL defines the four tables:

/* Drop and create four tables. */
DROP TABLE IF EXISTS one, two, three, four;
CREATE TABLE one   ( id int primary key auto_increment, msg varchar(10));
CREATE TABLE two   ( id int primary key auto_increment, msg varchar(10));
CREATE TABLE three ( id int primary key auto_increment, msg varchar(10));
CREATE TABLE four  ( id int primary key auto_increment, msg varchar(10));

Unfortunately, there’s no way to simply transaction management from the MySQL Command-Line Interface (CLI) because you need to build the logic that manages success and failure. It requires that you create a procedure using MySQL’s SQL/PSM (Persistent Stored Module) or another imperative programming language. You might think why can’t you just write an anonymous block program, like you can do in other stored procedural languages. The answer is simple. You can’t write anonymous blocks in MySQL’s SQL/PSM because they adhere to ANSI SQL-2003 (or more accurately ISO/IEC 9075-4:2003).

The following code block does:

  • Conditionally drops the locking() procedure.
  • Sets the default semicolon (;) delimiter to a double-dollar ($$), which lets you use the semicolon as statement and block terminators.
  • Declares a locking() procedure with the following:
    • Sets a parameter list with four IN-mode parameters.
    • Declares an EXIT handler that undoes any writes before an error in a sequence of DDL commands, like the INSERT, UPDATE, or DELETE statements. The EXIT handler then aborts completion of the rest of the procedure. (MySQL 13.6.7.2 Declare … Handler Statement)
    • Disables autocommit in the scope of the session.
    • Starts a transaction context and inserts data into four tables as a transaction. The continue handler picks up processing when one of the INSERT statements fails with a 1406 error code. The 1406 error code represents an error that occurs because the data is too long for a column’s width.
    • When all elements of the procedure complete, you commit the work.
  • Sets the double-dollar delimiter back to the default semicolon.
/* Conditionally drop procedure. */
DROP PROCEDURE IF EXISTS locking;
 
/* Set delimiter to $$ to allow ; inside the procedure. */
DELIMITER $$
 
/* Create a transaction procedure. */
CREATE PROCEDURE locking(IN pv_one   varchar(10)
                        ,IN pv_two   varchar(10)
                        ,IN pv_three varchar(10)
                        ,IN pv_four  varchar(10))
  BEGIN
    /* Declare an EXIT Handler when a string is too long
       for a column. Undo all prior writes with a ROLLBACK
       statement. */
    DECLARE EXIT HANDLER FOR 1406 
      BEGIN
        ROLLBACK;
      END;
 
    /* Disable autocommit. */
    SET AUTOCOMMIT=0;
 
    /* Start transaction scope. */	   
    START TRANSACTION;
 
    /* A series of INSERT statement. */
    INSERT INTO one   (msg) VALUES (pv_one);
    INSERT INTO two   (msg) VALUES (pv_two);
    INSERT INTO three (msg) VALUES (pv_three);
    INSERT INTO four  (msg) VALUES (pv_four);
 
    /* Commit transaction set. */
    COMMIT;
  END;
$$ 
 
/* Reset delimiter to ; for SQL statements. */
DELIMITER ;

The next block tests the locking() procedure. The first and third calls are successful but the second one fails because the third parameter is too long for the msg column in the three table. The error triggers the EXIT handler in the locking() procedure.

/* Call locking procedure. */
CALL locking('Donald','Goofy','Mickey','Pluto');
CALL locking('Squirrel','Chipmunk','Monkey business','Raccoon');
CALL locking('Curly','Larry','Moe','Shemp');

The query block below:

/* Select from tables, which should be empty. */
SELECT * FROM one;
SELECT * FROM two;
SELECT * FROM three;
SELECT * FROM four;

Returns the following, which shows only the first and third test cases succeed:

+----+--------+
| id | msg    |
+----+--------+
|  1 | Donald |
|  2 | Curly  |
+----+--------+
2 rows in set (0.01 sec)
 
+----+-------+
| id | msg   |
+----+-------+
|  1 | Goofy |
|  2 | Larry |
+----+-------+
2 rows in set (0.00 sec)
 
+----+--------+
| id | msg    |
+----+--------+
|  1 | Mickey |
|  2 | Moe    |
+----+--------+
2 rows in set (0.00 sec)
 
+----+-------+
| id | msg   |
+----+-------+
|  1 | Pluto |
|  2 | Shemp |
+----+-------+
2 rows in set (0.00 sec)

As always, I hope this helps those trying to write transactions across multiple tables.

Written by maclochlainn

March 16th, 2021 at 10:01 am

Posted in LAMP,Linux,Mac,MySQL,MySQL 8,MySQL Client,MySQL Shell,sql,Unix,Windows 10

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Oxygen XML Editor

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Somebody asked me about how they could convert an XML file to a CSV file to upload into MySQL. They were asking the question based on an old Convert XML to CSV blog post from 2008. Amazing though that is, I had to explain the process no longer requires manual tasks, like calling Java files from the Apache XML Project. All they needed to do was use the Oxygen XML Editor, which is why I wrote this blog post.

For example, I had them use the same sample XML file from the old blog post (shown below) with one change. The encoding value needs to change from latin1 (ISO-8859-1) to unicode (UTF-8). Then, they should put it into a local Windows directory (mine went into the C:\Data directory).

<?xml version="1.0" encoding="UTF-8"?>
<character>
  <name>
    <role>Indiana Jones</role>
    <actor>Harrison Ford</actor>
    <part>protagonist</part>
    <film>Indiana Jones and Raiders of the Lost Ark</film>
    <film>Indiana Jones and the Temple of Doom</film>
    <film>Indiana Jones and the Last Crusade</film>
    <film>Indiana Jones and the Kingdom of the Crystal Skull</film>
  </name>
  <name>
    <role>Wilhelmina Scott</role>
    <actor>Kate Capshaw</actor>
    <part>support</part>
    <film>Indiana Jones and the Temple of Doom</film>
  </name>
  <name>
    <role>Marion Ravenwood</role>
    <actor>Karen Allen</actor>
    <part>support</part>
    <film>Indiana Jones and Raiders of the Lost Ark</film>
    <film>Indiana Jones and the Kingdom of the Crystal Skull</film>
  </name>
  <name>
    <role>Elsa Schneider</role>
    <actor>Alison Doody</actor>
    <part>support</part>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Short Round</role>
    <actor>Jonathan Ke Quan</actor>
    <part>support</part>
    <film>Indiana Jones and the Temple of Doom</film>
  </name>
  <name>
    <role>Sallah</role>
    <actor>Jonn Rhys-Davies</actor>
    <part>support</part>
    <film>Indiana Jones and Raiders of the Lost Ark</film>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Professor Henry Jones</role>
    <actor>Sean Connery</actor>
    <part>support</part>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Henry "Mutt" Williams</role>
    <actor>Shia LaBeouf</actor>
    <part>support</part>
    <film>Indiana Jones and the Kingdom of the Crystal Skull</film>
  </name>
  <name>
    <role>Marcus Brody</role>
    <actor>Denholm Elliott</actor>
    <part>support</part>
    <film>Indiana Jones and Raiders of the Lost Ark</film>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Amrish Puri</role>
    <actor>Mola Ram</actor>
    <part>antagonist</part>
    <film>Indiana Jones and the Temple of Doom</film>
  </name>
  <name>
    <role>Rene Belloq</role>
    <actor>Belloq</actor>
    <part>antagonist</part>
    <film>Indiana Jones and Raiders of the Lost Ark</film>
  </name>
  <name>
    <role>Walter Donovan</role>
    <actor>Julian Glover</actor>
    <part>antagonist</part>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Colonel Vogel</role>
    <actor>Michael Bryne</actor>
    <part>antagonist</part>
    <film>Indiana Jones and the Last Crusade</film>
  </name>
  <name>
    <role>Irina Spalko</role>
    <actor>Cate Blanchett</actor>
    <part>antagonist</part>
    <film>Indiana Jones and the Kingdom of the Crystal Skull</film>
  </name>
</character>

Then, I had them copy the following XML Style Language Transformation (XSLT) file into the same C:\Data directory with the encoding value change from latin1 to unicode:

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<?xml version="1.0" encoding="UTF-8"?>
<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
<xsl:template match="/">
  <!-- This loops through the branch when a sibling meets a condition. -->
  <xsl:for-each select="character/name[film='Indiana Jones and the Last Crusade']">
  <!-- Sorts based on the value in the "role" element. -->
  <xsl:sort select="role" />
  <!-- Eliminates anyone that has a "part" element value of "antagonist". -->
    <xsl:if test="part != 'antagonist'">
      <!-- An apostrophe before and after with a line return. -->
      <xsl:text>&#39;</xsl:text>
      <xsl:value-of select="role"/>
      <!-- An apostrophe followed by a comma -->
      <xsl:text>&#39;&#44;</xsl:text>
      <xsl:text>&#39;</xsl:text>
      <xsl:value-of select="actor"/>
      <xsl:text>&#39;&#44;</xsl:text>
      <xsl:text>&#39;</xsl:text>
      <xsl:value-of select="film"/>
      <!-- An apostrophe followed by a line return -->
      <xsl:text>&#39;&#10;</xsl:text>
    </xsl:if>
  </xsl:for-each>
</xsl:template>
</xsl:stylesheet>

Open or launch the Oxygen XML Editor and do these steps:

  • Create a new Project called character.
  • Create the C:\Data\test.xml and C:\Data\convert.xsl files in a C:\Data directory.
  • Open the C:\Data\test.xml and C:\Data\convert.xsl files inside the Oxygen XML Editor.
  • Click on convert.xsl file tab before clicking on the Configure Transformation Scenario(s) button. The button looks like a red wrench with a small red arrow to the bottom right.
  • After launching the Configure Transformation Scenario(s) dialog, click the Edit button in the dialog box and launch the Edit Scenario dialog.
  • Enter file:/C:/Data/test.xml (use the file chooser if don’t want to type it) in the XML URL field in the Edit Scenario dialog.
  • Click the OK button to close the Edit Scenario dialog and the Apply associated button to close the Configure Transformation Scenario(s) dialog.
  • Click the Apply Transformation Scenario button, which is red arrow button. It will transform the XML document into a result pane at the bottom.
  • Select All (or Ctrl+A) in the result panel and right click on that selected area to launch a context sensitive menu. In that menu, click the Save button to launch a file chooser that will let you save your results.

If you know how to write XSLT this is simple and if you don’t it might take a little time to find a working example on the Internet. Better yet, check out the w3schools for the XSLT documentation or tutorials point’s Learn XSLT website. You can see how to Upload the CSV file into MySQL on this older blog post.

In Linux, you can make this conversion using the Command-Line Interface (CLI) by using the xsltproc program. Assume the XML file is test.xml and the XSLT file is tocsv.xsl, then you can generate the Comma-Separated Values file with this syntax:

xsltproc tocsv.xsl test.xml > text.csv

As always, I hope this helps those looking for a simple solution.

Written by maclochlainn

March 11th, 2021 at 1:15 pm

Posted in Apache,MySQL,MySQL 8,Oxygen XML Editor,xml,xslt

Tagged with , ,

MySQL Join Tutorial

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Some believe the most important part of SQL is the ability to query data. Queries typically retrieve data by joining many tables together into useful result sets. This tutorial takes the position that visibility into the data helps those new to SQL understand how joins work. To that end, the queries use Common Tabular Expressions (CTEs) instead of tables.

Default behavior of a JOIN without a qualifying descriptor is not simple because it may return:

  • A CROSS JOIN (or Cartesian Product) when there is no ON or USING subclause, or
  • An INNER JOIN when you use an ON or USING subclause.

The following query uses JOIN without a qualifier or an ON or USING subclause. It also uses two copies of the single CTE, which is more or less a derived table and the result of a subquery held in memory. This demonstrates the key reason for table aliases. That key reason is you can put two copies of the same table in memory under different identifiers or labels.

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WITH alpha AS
 (SELECT 'A' AS letter, 130 AS amount
  UNION
  SELECT 'B' AS letter, 150 AS amount
  UNION
  SELECT 'C' AS letter, 321 AS amount)
SELECT * FROM alpha a JOIN alpha b;

It returns a Cartesian product:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    130 |
| B      |    150 | A      |    130 |
| C      |    321 | A      |    130 |
| A      |    130 | B      |    150 |
| B      |    150 | B      |    150 |
| C      |    321 | B      |    150 |
| A      |    130 | C      |    321 |
| B      |    150 | C      |    321 |
| C      |    321 | C      |    321 |
+--------+--------+--------+--------+
9 rows in set (0.00 sec)

By adding an ON clause to line 8, the default JOIN keyword returns an INNER JOIN result.

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WITH alpha AS
 (SELECT 'A' AS letter, 130 AS amount
  UNION
  SELECT 'B' AS letter, 150 AS amount
  UNION
  SELECT 'C' AS letter, 321 AS amount)
SELECT * FROM alpha a JOIN alpha b
ON a.letter = b.letter;

It displays results, like:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    130 |
| B      |    150 | B      |    150 |
| C      |    321 | C      |    321 |
+--------+--------+--------+--------+
3 rows in set (0.00 sec)

The next example uses two CTEs. One uses letters 'A', 'B', 'C', and D and the other uses letters 'A', 'B', 'C', and 'E'. The letter D only exists in the alpha derived table and the letter 'E' only exists in the beta derived table. The amount column values differ for their respective letters in the two CTE tables.

The basic query below the comma delimited CTEs joins the alpha and beta derived tables with an INNER JOIN using an ON clause based on the letter column values found in both alpha and beta CTEs.

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WITH alpha AS
 (SELECT 'A' AS letter, 130 AS amount
  UNION
  SELECT 'B' AS letter, 150 AS amount
  UNION
  SELECT 'C' AS letter, 321 AS amount
  UNION
  SELECT 'D' AS letter, 783 AS amount)
, beta AS
 (SELECT 'A' AS letter, 387 AS amount
  UNION
  SELECT 'B' AS letter, 268 AS amount
  UNION
  SELECT 'C' AS letter, 532 AS amount
  UNION
  SELECT 'E' AS letter, 391 AS amount)
SELECT * FROM alpha a INNER JOIN beta b
ON a.letter = b.letter;

The INNER JOIN returns only those rows in alpha and beta CTEs where the letter column values match:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    387 |
| B      |    150 | B      |    268 |
| C      |    321 | C      |    532 |
+--------+--------+--------+--------+
3 rows in set (0.01 sec)

If you change line 17 from an INNER JOIN to a LEFT JOIN, you return all the rows from the alpha CTE and only those rows from the beta CTE that have a matching letter column value. The new line 17 for a LEFT JOIN is:

17

SELECT * FROM alpha a LEFT JOIN beta b

It returns the three matching rows plus the one non-matching row from the alpha CTE that is on the left side of the LEFT JOIN operator. You should note that that a left outer join puts null values into the beta CTE columns where there is no matching row for the 'D' letter found in the alpha CTE.

The results are shown below:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    387 |
| B      |    150 | B      |    268 |
| C      |    321 | C      |    532 |
| D      |    783 | NULL   |   NULL |
+--------+--------+--------+--------+
4 rows in set (0.01 sec)

If you change line 17 from an LEFT JOIN to a RIGHT JOIN, you return all the rows from the beta CTE and only those rows from the alpha CTE that have a matching letter column value. The new line 17 for a RIGHT JOIN is:

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SELECT * FROM alpha a RIGHT JOIN beta b

It returns the following result set:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    387 |
| B      |    150 | B      |    268 |
| C      |    321 | C      |    532 |
| NULL   |   NULL | E      |    391 |
+--------+--------+--------+--------+
4 rows in set (0.00 sec)

MySQL does not support a FULL JOIN operation but you can mimic a full join by combining a LEFT JOIN and RIGHT JOIN with the UNION operator. The UNION operator performs a unique sort operation, which reduces the two copies of matching rows returned by both the left and right join operation to a unique set.

This is the way to write the equivalent of a full join:

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WITH alpha AS
 (SELECT 'A' AS letter, 130 AS amount
  UNION
  SELECT 'B' AS letter, 150 AS amount
  UNION
  SELECT 'C' AS letter, 321 AS amount
  UNION
  SELECT 'D' AS letter, 783 AS amount)
, beta AS
 (SELECT 'A' AS letter, 387 AS amount
  UNION
  SELECT 'B' AS letter, 268 AS amount
  UNION
  SELECT 'C' AS letter, 532 AS amount
  UNION
  SELECT 'E' AS letter, 391 AS amount)
SELECT * FROM alpha LEFT JOIN beta
ON alpha.letter = beta.letter
UNION
SELECT * FROM alpha right JOIN beta
ON alpha.letter = beta.letter;

It returns one copy of the matching rows, and the non-matching rows from both the alpha and beta CTEs:

+--------+--------+--------+--------+
| letter | amount | letter | amount |
+--------+--------+--------+--------+
| A      |    130 | A      |    387 |
| B      |    150 | B      |    268 |
| C      |    321 | C      |    532 |
| D      |    783 | NULL   |   NULL |
| NULL   |   NULL | E      |    391 |
+--------+--------+--------+--------+
5 rows in set (0.00 sec)

A NATURAL JOIN would return no rows because it works by implicitly discovering columns with matching names in both CTEs and then joins the result set from both CTEs. While the letter column matches rows between the CTEs the amount column doesn’t hold any matches. The combination of letter and amount columns must match for a NATURAL JOIN operation to return any rows.

You also have the ability to override the cost optimizer and force a left to right join by using the STRAIGHT_JOIN operator. As always, I hope this helps those looking for a solution with an explanation.

Written by maclochlainn

January 26th, 2021 at 10:55 pm

Posted in MySQL,MySQL 8,sql

Tagged with

MySQL Membership

without comments

MySQL membership conditions are in the MySQL 8 Documentation. They’re found in the 13.2.11.3 Subqueries with ANY, IN, or SOME section. The IN and =ANY operators both perform equality matches with one twist. The IN operator works with a set of values or a subquery but the =ANY operator only works with a subquery.

I created the digits, letters, and words tables for this example. They hold the following values respectively:

  • The numbers table holds the values of 1, 2, 3, and 4
  • The letters table holds the values of 'a', 'b', 'c', and 'd'
  • The words table holds the values of 'Captain America', 'Iron Man', 'Thor', and Ant-Man

The following examples show the IN and =ANY membership comparison operators:

The IN membership operator:

The first example shows you how to use the IN operator with a set of values and the second example shows you how to use the IN operator with a subquery:

SELECT 'True Statement' AS result
WHERE  'a' IN ('a','b','c','d');
SELECT 'True Statement' AS result
WHERE  'a' IN (SELECT letter FROM letters);

The previous evaluations are case insensitive membership comparisons against a set of values and a return set from a subquery. You can make a case sensitive membership comparison by putting the BINARY keyword before one of the strings in a comparison. The BINARY keyword converts the string to a binary string and forces a binary string comparison of the two strings (MySQL 8.0 Reference Manual: 12.8.1 – String Comparison Operators and Functions).

SELECT 'True Statement' AS result
WHERE   BINARY 'a' IN (SELECT letter FROM letters);

The =ANY membership operator:

The same approach doesn’t work when you try to perform a membership comparison against a result set:

SELECT 'True Statement' AS result
WHERE  'a' =ANY ('a','b','c','d');

It returns the following error because the ANY, SOME, and ALL membership operators only work with subqueries. They all fail when you try to have them work with sets:

ERROR 1064 (42000): You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ''a','b','c','d')' at line 2

The following math operators work with the ANY, SOME, and ALL membership operators:

  • >
  • >=
  • <
  • <=
  • <>
  • !=

While the ANY and SOME membership operators work alike, the AND operator works differently. The ANY and SOME membership operators work like an OR logical operator in the WHERE clause.

For example, the following <ANY comparison works when the right operand is in the set but not the largest element returned by the subquery.

SELECT 'True Statement' AS result
WHERE  2 <SOME (SELECT digit FROM numbers);

You can use a <=ANY or <=SOME when the left operand is equal to the highest digit in the subquery’s result set. The <ALL comparison only works when the left operand is a digit lower than the smallest element returned by the subquery.

SELECT 'True Statement' AS result
WHERE   0 <ALL (SELECT digit FROM numbers);

Here’s a set of SQL commands to setup the test cases for membership operators:

DROP TABLE letters;
CREATE TABLE letters (letter VARCHAR(10));
DROP TABLE numbers;
CREATE TABLE numbers (digit int);
DROP TABLE words;
CREATE TABLE words (word VARCHAR(20));
INSERT INTO letters VALUES ('a'),('b'),('c'),('d'),('e');
INSERT INTO numbers VALUES (1),(2),(3),(4),(5);
INSERT INTO words VALUES ('Captain America'),('Thor'),('Iron Man'),('Ant-Man');

As always, I hope this helps those looking for more examples and good solutions.

Written by maclochlainn

January 24th, 2021 at 1:25 am

Posted in macOS,MySQL 8,sql

Tagged with

MySQL macOS Docker

without comments

While you can download MySQL as a DMG package, a number of users would prefer to install it as a Docker instance. You won’t find the macOS downloads on the same web site as other downloads. You can use the following macOS download site.

After installing Docker on your macOS, you can pull a copy of the current MySQL Server with the following command:

docker pull mysql/mysql-server

You should create a mysql directory inside your ~/Documents directory with this command:

mkdir ~/Documents/mysql

Then, you should use the cd command to change into the ~/Documents/mysql directory and run this command:

pwd

It should return the following directory:

/Users/<user_name>/Documents/mysql

Use the /Users/<user_name>/Documents/mysql as the in this command:

docker run --name=mysql1 --volume=<path_to_folder>:/var/lib/mysql -p 33060:3306/tcp -d mysql/mysql-server

The --name option value is mysql1 and it becomes the container value. Docker mounts the column in the ~/Documents/mysql folder. All data from the Docker container under the /var/lib/mysql directory will persist in this directory. This directory will still contain the database when the container is shut down.

The docker run command maps the localhost’s 33060 port to the 3306 port on the Docker container. You will use the 33060 port to connect to the Docker instance of MySQL. It raises a dialog box asking for permission to access the directory. You need to allow Docker to write to the ~/Documents/mysql directory.

You can verify that the Docker container is running with the following command:

docker ps

It should return:

CONTAINER ID   IMAGE                COMMAND                  CREATED         STATUS                   PORTS                                      NAMES
142b5c491cd8   mysql/mysql-server   "/entrypoint.sh mysq…"   7 minutes ago   Up 6 minutes (healthy)   33060-33061/tcp, 0.0.0.0:33060->3306/tcp   mysql1

You can get the MySQL generated root password with this Docker command:

docker logs mysql1 2>&1 | grep GENERATED

It returns something like the following:

[Entrypoint] GENERATED ROOT PASSWORD: vop#3GNYqK3nC@S@N3haf3nox5E

Use the following Docker command to connect to the Docker container:

docker exec -it mysql1 /bin/bash

It launches a Bash shell inside the Docker container:

bash-4.2#

Start the mysql Command-Line Interface (CLI):

mysql -uroot -p

You are then prompted for a password:

Enter password:

After successfully entering the password, you’ll see the following:

Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 55
Server version: 8.0.22
 
Copyright (c) 2000, 2020, Oracle and/or its affiliates. All rights reserved.
 
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
 
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
 
mysql>

Unless you want to remember that hugely complex root password, you should consider changing it to something simple like, 'cangetin' with the following command:

ALTER USER 'root'@'localhost' IDENTIFIED WITH MYSQL_NATIVE_PASSWORD BY 'cangetin';

Next, you should check for the installed databases with this command:

show databases;

It will return:

+--------------------+
| Database           |
+--------------------+
| information_schema |
| mysql              |
| performance_schema |
| sys                |
+--------------------+
4 rows in set (0.01 sec)

Exiting mysql, you can see the contents of the root user’s directory with this list command:

ls -al

It should return:

total 84
drwxr-xr-x   1 root root 4096 Jan 12 03:41 .
drwxr-xr-x   1 root root 4096 Jan 12 03:41 ..
-rwxr-xr-x   1 root root    0 Jan 12 03:41 .dockerenv
lrwxrwxrwx   1 root root    7 Oct 12 22:06 bin -> usr/bin
dr-xr-xr-x   2 root root 4096 Apr 11  2018 boot
drwxr-xr-x   5 root root  340 Jan 12 03:41 dev
drwxr-xr-x   2 root root 4096 Oct 19 05:47 docker-entrypoint-initdb.d
-rwxr-xr-x   1 root root 7496 Oct 19 05:37 entrypoint.sh
drwxr-xr-x   1 root root 4096 Jan 12 03:41 etc
-rw-r--r--   1 root root   86 Jan 12 03:41 healthcheck.cnf
-rwxr-xr-x   1 root root 1073 Oct 19 05:37 healthcheck.sh
drwxr-xr-x   2 root root 4096 Apr 11  2018 home
lrwxrwxrwx   1 root root    7 Oct 12 22:06 lib -> usr/lib
lrwxrwxrwx   1 root root    9 Oct 12 22:06 lib64 -> usr/lib64
drwxr-xr-x   2 root root 4096 Apr 11  2018 media
drwxr-xr-x   2 root root 4096 Apr 11  2018 mnt
-rw-r--r--   1 root root    0 Jan 12 03:41 mysql-init-complete
drwxr-xr-x   2 root root 4096 Apr 11  2018 opt
dr-xr-xr-x 127 root root    0 Jan 12 03:41 proc
dr-xr-x---   1 root root 4096 Jan 12 04:21 root
drwxr-xr-x   1 root root 4096 Oct 19 05:47 run
lrwxrwxrwx   1 root root    8 Oct 12 22:06 sbin -> usr/sbin
drwxr-xr-x   2 root root 4096 Apr 11  2018 srv
dr-xr-xr-x  13 root root    0 Jan 12 03:41 sys
drwxrwxrwt   1 root root 4096 Jan 12 03:41 tmp
drwxr-xr-x   1 root root 4096 Oct 12 22:06 usr
drwxr-xr-x   1 root root 4096 Oct 12 22:06 var

At this point, you have to make a choice about how you will access the MySQL database. You have a couple options:

  • Create an individual student user that can access the MySQL-Server as a micro-service, which would only be a MySQL user connecting through MySQL workbench. At least, that’s the only connection option unless you likewise install the mysql client on your host macOS. The mysql client lets you connect from the host operating system through the Command-Line Interface (CLI).
  • Create a local student user account inside the Docker container. It will have access to the container file system and mimic the behavior of a non-root user on a server.

Let’s create both for this demonstration. Reconnect as the root user and issue the following two commands:

CREATE USER 'student'@'localhost' IDENTIFIED WITH MYSQL_NATIVE_PASSWORD BY 'student';
CREATE USER 'student'@'%.%.%.%'   IDENTIFIED WITH MYSQL_NATIVE_PASSWORD BY 'student';

The first version of the student user lets you access the database from inside the Docker container. The second version of the student user lets you access the database from MySQL Workbench deployed on your base macOS.

You can add a sakila database and grant all privileges to the student user with the following command as the root user:

CREATE DATABASE sakila;
GRANT ALL ON sakila.* TO 'student'@'localhost';
GRANT ALL ON sakila.* TO 'student'@'%.%.%.%';

You need to get the sakila database from the Internet within the Docker container. Exit the mysql client with the following command:

quit;

As the root user, install the wget and tar Linux utilities with this command:

yum install -y wget tar

As the student user, you can use the wget command to grab a copy of the sakila database and store the database locally. Use the cd command to get to your ${HOME} directory, like:

cd

Use this syntax to get a copy of the sakila database:

wget http://downloads.mysql.com/docs/sakila-db.tar.gz

Use the ls command to verify the download, then run the following set of Linux commands from the Linux CLI:

tar -xzf sakila-db.tar.gz
cd sakila-db

Run the following two commands from the sakila-db directory:

mysql -ustudent -p < sakila-schema.sql
mysql -ustudent -p < sakila-data.sql

or, you can connect as the student user to the MySQL client and run them there:

source sakila-schema.sql
source sakila-data.sql

You create a non-root student user for the Docker container from the macOS host opearting system. Which means you need to quit; the mysql client, and exit the root user’s session with the Docker container.

At the terminal in your macOS, issue the following Docker command to create a student account in the mysql1 container:

docker exec mysql1 bash -c "useradd -u 501 -g mysql -G users \
>      -d /home/student -s /bin/bash -c "Student" -n student"

Now, you can connect as the student user to the mysql1 container, with the following Docker command:

docker exec -it --user student mysql1 bash

The first time you connect, you will be a the / (root) directory. Use the following cd command to go to the student user’s home directory:

cd

Then, type the following command to set the student user’s home directory as the default. You need to use this command because vim isn’t installed in the default Docker container, which would let you interactively edit files. It appends the necessary Bash shell command to the end of the .bashrc file.

echo 'cd ${HOME}' >> .bashrc

With this change, the student user will always be available form its home directory next time you connect to the mysql1 container. You can use scp to move files into the student user’s home (/home/student) directory. However, you can create a quick test.sql file like this:

echo "select user();" > test.sql

Connect to the mysql CLI with as the student user:

mysql -ustudent -p

Call your test.sql file from the Linux CLI, like:

mysql -ustudent -p < test.sql

or, you can run the test.sql program as follows form the MySQL command-line:

source test.sql

It will return:

+-------------------+
| user()            |
+-------------------+
| student@localhost |
+-------------------+
1 row in set (0.00 sec)

That’s the basic setup of the Docker MySQL Container on the macOS. You can do much more once you’ve configured it like this. For example, you can add vim to your library repository as the root user with the following command:

yum install -y vim

It just takes a minute or a bit more. Adding vim opens up so much flexibility for you inside the Docker container, it’s impossible for me to resist. 😉

Written by maclochlainn

January 11th, 2021 at 10:20 pm

Posted in Docker,Linux,Mac,Mac OS X,macOS,MySQL,MySQL 8,MySQL Client,MySQL Workbench,sql

Tagged with ,

MySQL sakila Database

without comments

While I thought my instructions were clear, it appears there should have been more in my examples for using the MySQL MSI. A key thing that happened is that students opted not to install:

Samples and Examples 8.0.22

Unfortunately, they may not have read the Preface of Alan Beaulieu’s Learning SQL, 3rd Edition where he explains how to manually download the files from the MySQL web site. Here are those, very clear, instructions (pg. XV) with my additions in italics for the MySQL Shell:

First, you will need to launch the mysql command-line client or the mysqlsh command-line shell, and provide a password, and then perform the following steps:

  1. Go to https://dev.mysql.com/doc/index-other.html and download the files for the “sakila database” under the Example Database section.
  2. Put the files in the local directory such as C:\temp\sakila-db (used for the next two steps, but overwrite with your directory path).
  3. Type 

    source c:\temp\sakila-db\sakila-schema.sql

    and press enter.

  4. Type 

    source c:\temp\sakila-db\sakila-data.sql

    and press enter.

These instructions let you create the sakila database without rerunning the MSI to add a product. Naturally, you can avoid these steps by using the GUI approach provided in the MySQL MSI file.

As always, I hope this helps those looking for how to solve problems.

Written by maclochlainn

January 9th, 2021 at 11:22 am

Posted in Database Design,DBA,MySQL,MySQL 8,MySQL Client,MySQL Shell,MySQL Workbench,Windows 10,Windows OS

Tagged with ,

MySQL Self-Join

with 4 comments

I’m switching to MySQL and leveraging Alan Beaulieu’s Learning SQL as a supporting reference for my Database Design and Development course. While reviewing Alan’s Chapter 5: Querying Multiple Tables, I found his coverage of using self-joins minimal.

In fact, he adds a prequel_film_id column to the film table in the sakila database and then a single row to demonstrate a minimal self-join query. I wanted to show them how to view a series of rows interconnected by a self-join, like the following:

SELECT   f.title AS film
,        fp.title AS prequel
FROM     film f LEFT JOIN film fp
ON       f.prequel_id = fp.film_id
WHERE    f.series_name = 'Harry Potter'
ORDER BY f.series_number;

It returns the following result set:

+----------------------------------------------+----------------------------------------------+
| film                                         | prequel                                      |
+----------------------------------------------+----------------------------------------------+
| Harry Potter and the Chamber of Secrets      | Harry Potter and the Sorcerer's Stone        |
| Harry Potter and the Prisoner of Azkaban     | Harry Potter and the Chamber of Secrets      |
| Harry Potter and the Goblet of Fire          | Harry Potter and the Prisoner of Azkaban     |
| Harry Potter and the Order of the Phoenix    | Harry Potter and the Goblet of Fire          |
| Harry Potter and the Half Blood Prince       | Harry Potter and the Order of the Phoenix    |
| Harry Potter and the Deathly Hallows: Part 1 | Harry Potter and the Half Blood Prince       |
| Harry Potter and the Deathly Hallows: Part 2 | Harry Potter and the Deathly Hallows: Part 1 |
+----------------------------------------------+----------------------------------------------+
7 rows in set (0.00 sec)

Then, I thought about what questions the students might ask. For example, why doesn’t the query return the first film that doesn’t have a prequel. So, I took the self-join to the next level to display the first film having no prequel, like this:

SELECT   f.title AS film
,        IFNULL(
           CASE
             WHEN NOT f.film_id = fp.film_id
             AND      f.prequel_id = fp.film_id THEN fp.title		   
           END,'None') AS prequel
FROM     film f LEFT JOIN film fp
ON       f.prequel_id = fp.film_id
WHERE    f.series_name = 'Harry Potter'
ORDER BY f.series_number;

The CASE operator in the SELECT-list filters the result set by eliminating rows erroneously returned. Without the CASE filter, the query would return the original Harry Potter and the Sorcerer’s Stone film matched agains a NULL and all of the other sequels. The CASE operator effectively limits the result set for the LEFT JOIN to only the following data:

+----------------------------------------------+----------------------------------------------+
| film                                         | prequel                                   |
+----------------------------------------------+----------------------------------------------+
| Harry Potter and the Sorcerer's Stone        | NULL                                         |
+----------------------------------------------+----------------------------------------------+

The IFNULL() built-in function lets you replace the NULL value returned as the prequel’s title value. The IFNULL() function substitutes a 'None' string literal for a NULL value. The query returns the following result set:

+----------------------------------------------+----------------------------------------------+
| film                                         | prequel                                      |
+----------------------------------------------+----------------------------------------------+
| Harry Potter and the Sorcerer's Stone        | None                                         |
| Harry Potter and the Chamber of Secrets      | Harry Potter and the Sorcerer's Stone        |
| Harry Potter and the Prisoner of Azkaban     | Harry Potter and the Chamber of Secrets      |
| Harry Potter and the Goblet of Fire          | Harry Potter and the Prisoner of Azkaban     |
| Harry Potter and the Order of the Phoenix    | Harry Potter and the Goblet of Fire          |
| Harry Potter and the Half Blood Prince       | Harry Potter and the Order of the Phoenix    |
| Harry Potter and the Deathly Hallows: Part 1 | Harry Potter and the Half Blood Prince       |
| Harry Potter and the Deathly Hallows: Part 2 | Harry Potter and the Deathly Hallows: Part 1 |
+----------------------------------------------+----------------------------------------------+
8 rows in set (0.01 sec)

Alan’s modification of the sakila.film table had the following two related design flaws:

  • It didn’t provide a way to guarantee the ordering of films with prequels because relational databases don’t guarantee ordered result sets unless you use an ORDER BY clause, which typically requires a column to order.
  • It didn’t provide a way to isolate a series of films.

I modified the film table differently by adding the series_name, series_number, and prequel_id columns. The series_name column lets you group results and the series_number column lets you order by a preserved sequence that you store as part of the data The prequel_id column lets you connect to the prequel film, much like the backward portion of a doubly linked list.

The new sakila.film table is:

+----------------------+---------------------------------------------------------------------+------+-----+-------------------+-----------------------------------------------+
| Field                | Type                                                                | Null | Key | Default           | Extra                                         |
+----------------------+---------------------------------------------------------------------+------+-----+-------------------+-----------------------------------------------+
| film_id              | smallint unsigned                                                   | NO   | PRI | NULL              | auto_increment                                |
| title                | varchar(255)                                                        | NO   | MUL | NULL              |                                               |
| description          | text                                                                | YES  |     | NULL              |                                               |
| release_year         | year                                                                | YES  |     | NULL              |                                               |
| language_id          | tinyint unsigned                                                    | NO   | MUL | NULL              |                                               |
| original_language_id | tinyint unsigned                                                    | YES  | MUL | NULL              |                                               |
| rental_duration      | tinyint unsigned                                                    | NO   |     | 3                 |                                               |
| rental_rate          | decimal(4,2)                                                        | NO   |     | 4.99              |                                               |
| length               | smallint unsigned                                                   | YES  |     | NULL              |                                               |
| replacement_cost     | decimal(5,2)                                                        | NO   |     | 19.99             |                                               |
| rating               | enum('G','PG','PG-13','R','NC-17')                                  | YES  |     | G                 |                                               |
| special_features     | set('Trailers','Commentaries','Deleted Scenes','Behind the Scenes') | YES  |     | NULL              |                                               |
| last_update          | timestamp                                                           | NO   |     | CURRENT_TIMESTAMP | DEFAULT_GENERATED on update CURRENT_TIMESTAMP |
| series_name          | varchar(20)                                                         | YES  |     | NULL              |                                               |
| series_number        | int unsigned                                                        | YES  |     | NULL              |                                               |
| prequel              | int unsigned                                                        | YES  |     | NULL              |                                               |
+----------------------+---------------------------------------------------------------------+------+-----+-------------------+-----------------------------------------------+
16 rows in set (0.21 sec)

After adding the three new columns, I inserted eight rows for the original Harry Potter films. You can use the following script in the MySQL client (mysql) to add the columns and insert the data to test the preceding queries:

-- Use sakila database.
USE sakila;
 
-- Add a prequel_id column to the sakila.film table.
ALTER TABLE film
ADD (series_name    varchar(20)),
ADD (series_number  int unsigned),
ADD (prequel_id     int unsigned);
 
-- Set primary to foreign key local variable.
SET @sv_film_id = 0;
 
-- Insert Harry Potter films in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Sorcerer''s Stone'
,'A film about a young boy who on his eleventh birthday discovers, he is the orphaned boy of two powerful wizards and has unique magical powers.'
, 2001
, 1
, NULL
, 3
, 0.99
, 152
, 19.99
,'PG'
,'Trailers'
,'2001-11-04'
,'Harry Potter'
, 1
, NULL );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 2nd film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Chamber of Secrets'
,'A film where Harry returning to Hogwarts, still famous and a hero, when strange things start to happen ... people are turning to stone and no-one knows what, or who, is doing it.'
, 2002
, 1
, NULL
, 3
, 0.99
, 160
, 19.99
,'PG'
,'Trailers'
,'2002-11-15'
,'Harry Potter'
, 2
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 3rd film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Prisoner of Azkaban'
,'A film where Harry, Ron, and Hermione return for their third year at Hogwarts and are forced to face escaped prisoner, Sirius Black.'
, 2004
, 1
, NULL
, 3
, 0.99
, 141
, 19.99
,'PG'
,'Trailers'
,'2004-06-04'
,'Harry Potter'
, 3
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 4th film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Goblet of Fire'
,'A film where where Harry Potter''s name emerges from the Goblet of Fire, and he becomes a competitor in a grueling battle for glory among three wizarding schools - the Triwizard Tournament.'
, 2005
, 1
, NULL
, 3
, 0.99
, 157
, 19.99
,'PG'
,'Trailers'
,'2005-11-18'
,'Harry Potter'
, 4
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 5th film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Order of the Phoenix'
,'A film where Lord Voldemort has returned, but the Ministry of Magic is doing everything it can to keep the wizarding world from knowing the truth.'
, 2007
, 1
, NULL
, 3
, 0.99
, 138
, 19.99
,'PG-13'
,'Trailers'
,'2007-07-12'
,'Harry Potter'
, 5
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 6th film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Half Blood Prince'
,'A film where Voldemort is tightening his grip on Hogwarts and it is no longer the safe haven it once was. Harry and Dumbledore work to find the key to unlock the Dark Lord''s defenses.'
, 2009
, 1
, NULL
, 3
, 0.99
, 153
, 19.99
,'PG'
,'Trailers'
,'2009-07-15'
,'Harry Potter'
, 6
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 7th film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Deathly Hallows: Part 1'
,'A film where Harry, Ron and Hermione set out on their perilous mission to track down and destroy the Horcruxes - the keys to Voldemort''s immortality.'
, 2010
, 1
, NULL
, 3
, 0.99
, 146
, 19.99
,'PG-13'
,'Trailers'
,'2010-11-19'
,'Harry Potter'
, 7
, @sv_film_id );
 
-- Assign the last generated primary key value to the local variable.
SET @sv_film_id := last_insert_id();
 
-- Insert 8th film in sakila.film table with classic values clause.
INSERT INTO film
( title
, description
, release_year
, language_id
, original_language_id
, rental_duration
, rental_rate
, length
, replacement_cost
, rating
, special_features
, last_update
, series_name
, series_number
, prequel_id )
VALUES
('Harry Potter and the Deathly Hallows: Part 2'
,'A film where Harry, Ron and Hermione set out on their perilous mission to track down and destroy the Horcruxes - the keys to Voldemort''s immortality.'
, 2011
, 1
, NULL
, 3
, 0.99
, 130
, 19.99
,'PG-13'
,'Trailers'
,'2011-07-15'
,'Harry Potter'
, 8
, @sv_film_id );

You can put the following commands into a SQL script file to revert the sakila.film table to its base configuration:

DELETE FROM film WHERE film_id > 1000;
ALTER TABLE film DROP COLUMN series_name;
ALTER TABLE film DROP COLUMN series_number;
ALTER TABLE film DROP COLUMN prequel_id;
ALTER TABLE film AUTO_INCREMENT = 1000;

As always, I hope this helps those looking for how to solve a new problem.

Written by maclochlainn

November 22nd, 2020 at 4:03 pm

Posted in Database Design,DBA,DevOps,LAMP,Linux,Mac,macOS,MAMP,MySQL,MySQL 8,MySQL Client,sql

Tagged with ,

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