in this tutorial, We’ll learn about how to add add, edit, delete functionality using Bootstrap 5, PHP and MySQL.I am extending previous tutorial Ajax Pagination with Search and Sort. We have already added functionality to listing, searching, and sorting into datatable, So Let’s add functionality to CRUD operation without page refresh. We have already added […]
The post Ajax Datatable CRUD Operation Using PHP and MySQL appeared first on Phpflow.com.
For the MySQL Million Challenge, I was going through the server syntax in order to understand what things can be created in the server. And now my OCD triggered. DDL is a mess.
As a database developer, I want to be able to create server
objects using the CREATE thing syntax.
The server gives you that for the following things:
…
[Read more]For the MySQL Million Challenge, I was going through the server syntax in order to understand what things can be created in the server. And now my OCD triggered. DDL is a mess.
Creation
As a database developer, I want to be able to create server
objects using the CREATE thing syntax.
The server gives you that for the following things:
Safe creation
As a database developer I want to be able to script things
safely, so I need IF NOT EXISTS clauses in my
CREATE …
A long-standing idea that I have is to test the servers limits: How does it fail and break if there are very many of a thing? Previously that was too easy, because many structures were constructed in a way that it was obvious they would not scale. But with MySQL 8 many things were overhauled, so let’s see what we can make many of and see how the server fares.
Database servers are programs that are built to handle a lot of data. A million rows in a table are not a problem, and searching one in a million rows neither, because the server has structures that make this fast.
But is the database server using these structures internally in an efficient way and can it handle a lot of tables, schemas, views, users, grants, roles and so on?
What can we try?
A long-standing idea that I have is to test the servers limits: How does it fail and break if there are very many of a thing? Previously that was too easy, because many structures were constructed in a way that it was obvious they would not scale. But with MySQL 8 many things were overhauled, so let’s see what we can make many of and see how the server fares.
The Million Challenge
Database servers are programs that are built to handle a lot of data. A million rows in a table are not a problem, and searching one in a million rows neither, because the server has structures that make this fast.
But is the database server using these structures internally in an efficient way and can it handle a lot of tables, schemas, views, users, grants, roles and so on?
What can we try?
I frequently see requests on various web sites from MySQL novices looking for example databases with which to practice. There are several that are highly recommended and we will take a look at them over the next few weeks.
1. World Data Base -- See https://dev.mysql.com/doc/world-setup/en/
This has been THE database used in MySQL's documentation, classes, examples, and just about anything else. There are three tables -- city, country, and countrylanguage -- that are fantastic for teaching the basics such as JOINs, GROUP BY, HAVING, and other SQL commands.
1x. World X Database -- See https://dev.mysql.com/doc/world-x-setup/en/
With the advent of the X DevAPI there needed to be a test database with JSON columns and the World Database was modified. The countryinfo table was added to the inherited three so that you can practice with JSON columns and a JSON …
[Read more]I never had much reason to use table compression, so I largely ignored the topic in MySQL. I knew that MySQL had table compression since 5.1, but I also knew the implementation was horribly complicated and double stored all data. There is also page compression, a feature introduced with 5.7, which replaces table compression and works much better.
is available in MySQL 5.1 and newer. It is used by setting an
InnoDB table up with ROW_FORMAT=COMPRESSED
KEY_BLOCK_SIZE=8 or similar, for even smaller key block
sizes. A lot of status tables in
INFORMATION_SCHEMA.%CMP% are available to monitor
it.
Table compression creates smaller pages (in the size you specify with …
[Read more]I never had much reason to use table compression, so I largely ignored the topic in MySQL. I knew that MySQL had table compression since 5.1, but I also knew the implementation was horribly complicated and double stored all data. There is also page compression, a feature introduced with 5.7, which replaces table compression and works much better.
Table Compression
Table Compression is available in MySQL 5.1
and newer. It is used by setting an InnoDB table up with
ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8 or similar,
for even smaller key block sizes. A lot of status tables in
INFORMATION_SCHEMA.%CMP% are available to monitor
it.
Table compression creates smaller pages (in the size you specify
with KEY_BLOCK_SIZE), and loads and stores
compressed pages of this smaller size from and to the …
We observe a large number of messages of the kind
The table '../tmp/#sql…' is full
In older Versions of MySQL, implied temporary tables are being
created whenever your EXPLAIN contained the phrase
using temporary.
In this case, MySQL would create an in-memory temporary table to materialize an intermediate query result, and then continue to process the data from there. If that temporary table was larger than some configurable limit, the temporary table would instead be converted to a MyISAM table on disk, streamed out, and then work would continue with this.
This has a large number of disadvantages:
MEMORY storage engine can have no
variable length columns. That means, any VARCHAR
column gets converted to …We observe a large number of messages of the kind
The table '../tmp/#sql…' is full
Before MySQL 8
In older Versions of MySQL, implied temporary tables are being
created, whenever your EXPLAIN contained the phrase
using temporary.
In this case, MySQL would create an in-memory temporary table to materialize an intermediate query result, and then continue to process the data from there. If that temporary table was larger than some configurable limit, the temporary table would instead be converted to a MyISAM table on disk, streamed out, and then work would continue with this.
This has a large number of disadvantages:
MEMORY storage engine can have no
variable length columns. That means, any VARCHAR
column gets converted to a CHAR column in the
MEMORY version of that table.