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In this article, we are going to learn how we can update and delete data using Delete and Update statements. In my previous articles, we have learned how we can insert data using INSERT statement, and sort and filter data using WHERE and ORDER BY statements.
To demonstrate UPDATE and DELETE statements, I have restored the sakila database on MySQL Server. We are going to use the film and language table of the sakila database.
#mysql
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HTML to Markdown
MySQL is the all-time number one open source database in the world, and a staple in RDBMS space. DigitalOcean is quickly building its reputation as the developers cloud by providing an affordable, flexible and easy to use cloud platform for developers to work with. MySQL on DigitalOcean is a natural fit, but what’s the best way to deploy your cloud database? In this post, we are going to compare the top two providers, DigitalOcean Managed Databases for MySQL vs. ScaleGrid MySQL hosting on DigitalOcean.
At a glance – TLDR
ScaleGrid Blog - At a glance overview - 1st pointCompare Throughput
ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads. Read now
ScaleGrid Blog - At a glance overview - 2nd pointCompare Latency
On average, ScaleGrid achieves almost 30% lower latency over DigitalOcean for the same deployment configurations. Read now
ScaleGrid Blog - At a glance overview - 3rd pointCompare Pricing
ScaleGrid provides 30% more storage on average vs. DigitalOcean for MySQL at the same affordable price. Read now
MySQL DigitalOcean Performance Benchmark
In this benchmark, we compare equivalent plan sizes between ScaleGrid MySQL on DigitalOcean and DigitalOcean Managed Databases for MySQL. We are going to use a common, popular plan size using the below configurations for this performance benchmark:
Comparison Overview
ScaleGridDigitalOceanInstance TypeMedium: 4 vCPUsMedium: 4 vCPUsMySQL Version8.0.208.0.20RAM8GB8GBSSD140GB115GBDeployment TypeStandaloneStandaloneRegionSF03SF03SupportIncludedBusiness-level support included with account sizes over $500/monthMonthly Price$120$120
As you can see above, ScaleGrid and DigitalOcean offer the same plan configurations across this plan size, apart from SSD where ScaleGrid provides over 20% more storage for the same price.
To ensure the most accurate results in our performance tests, we run the benchmark four times for each comparison to find the average performance across throughput and latency over read-intensive workloads, balanced workloads, and write-intensive workloads.
Throughput
In this benchmark, we measure MySQL throughput in terms of queries per second (QPS) to measure our query efficiency. To quickly summarize the results, we display read-intensive, write-intensive and balanced workload averages below for 150 threads for ScaleGrid vs. DigitalOcean MySQL:
ScaleGrid MySQL vs DigitalOcean Managed Databases - Throughput Performance Graph
For the common 150 thread comparison, ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads.
#cloud #database #developer #digital ocean #mysql #performance #scalegrid #95th percentile latency #balanced workloads #developers cloud #digitalocean droplet #digitalocean managed databases #digitalocean performance #digitalocean pricing #higher throughput #latency benchmark #lower latency #mysql benchmark setup #mysql client threads #mysql configuration #mysql digitalocean #mysql latency #mysql on digitalocean #mysql throughput #performance benchmark #queries per second #read-intensive #scalegrid mysql #scalegrid vs. digitalocean #throughput benchmark #write-intensive
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First thing, we will need a table and i am creating products table for this example. So run the following query to create table.
CREATE TABLE `products` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
`description` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
`created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
`updated_at` datetime DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=7 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
Next, we will need to insert some dummy records in this table that will be deleted.
INSERT INTO `products` (`name`, `description`) VALUES
('Test product 1', 'Product description example1'),
('Test product 2', 'Product description example2'),
('Test product 3', 'Product description example3'),
('Test product 4', 'Product description example4'),
('Test product 5', 'Product description example5');
Now we are redy to create a model corresponding to this products table. Here we will create Product model. So let’s create a model file Product.php file under app directory and put the code below.
<?php
namespace App;
use Illuminate\Database\Eloquent\Model;
class Product extends Model
{
protected $fillable = [
'name','description'
];
}
Now, in this second step we will create some routes to handle the request for this example. So opeen routes/web.php file and copy the routes as given below.
routes/web.php
Route::get('product', 'ProductController@index');
Route::delete('product/{id}', ['as'=>'product.destroy','uses'=>'ProductController@destroy']);
Route::delete('delete-multiple-product', ['as'=>'product.multiple-delete','uses'=>'ProductController@deleteMultiple']);
#laravel #delete multiple rows in laravel using ajax #laravel ajax delete #laravel ajax multiple checkbox delete #laravel delete multiple rows #laravel delete records using ajax #laravel multiple checkbox delete rows #laravel multiple delete
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MySQL does not limit the number of slaves that you can connect to the master server in a replication topology. However, as the number of slaves increases, they will have a toll on the master resources because the binary logs will need to be served to different slaves working at different speeds. If the data churn on the master is high, the serving of binary logs alone could saturate the network interface of the master.
A classic solution for this problem is to deploy a binlog server – an intermediate proxy server that sits between the master and its slaves. The binlog server is set up as a slave to the master, and in turn, acts as a master to the original set of slaves. It receives binary log events from the master, does not apply these events, but serves them to all the other slaves. This way, the load on the master is tremendously reduced, and at the same time, the binlog server serves the binlogs more efficiently to slaves since it does not have to do any other database server processing.
Ripple is an open source binlog server developed by Pavel Ivanov. A blog post from Percona, titled MySQL Ripple: The First Impression of a MySQL Binlog Server, gives a very good introduction to deploying and using Ripple. I had an opportunity to explore Ripple in some more detail and wanted to share my observations through this post.
Ripple supports only GTID mode, and not file and position-based replication. If your master is running in non-GTID mode, you will get this error from Ripple:
Failed to read packet: Got error reading packet from server: The replication sender thread cannot start in AUTO_POSITION mode: this server has GTID_MODE = OFF instead of ON.
You can specify Server_id and UUID for the ripple server using the cmd line options: -ripple_server_id and -ripple_server_uuid
Both are optional parameters, and if not specified, Ripple will use the default server_id=112211 and uuid will be auto generated.
While connecting to the master, you can specify the replication user and password using the command line options:
-ripple_master_user and -ripple_master_password
You can use the command line options -ripple_server_ports and -ripple_server_address to specify the connection end points for the Ripple server. Ensure to specify the network accessible hostname or IP address of your Ripple server as the -rippple_server_address. Otherwise, by default, Ripple will bind to localhost and hence you will not be able to connect to it remotely.
You can use the CHANGE MASTER TO command to connect your slaves to replicate from the Ripple server.
To ensure that Ripple can authenticate the password that you use to connect to it, you need to start Ripple by specifying the option -ripple_server_password_hash
For example, if you start the ripple server with the command:
rippled -ripple_datadir=./binlog_server -ripple_master_address= <master ip> -ripple_master_port=3306 -ripple_master_user=repl -ripple_master_password='password' -ripple_server_ports=15000 -ripple_server_address='172.31.23.201' -ripple_server_password_hash='EF8C75CB6E99A0732D2DE207DAEF65D555BDFB8E'
you can use the following CHANGE MASTER TO command to connect from the slave:
CHANGE MASTER TO master_host='172.31.23.201', master_port=15000, master_password=’XpKWeZRNH5#satCI’, master_user=’rep’
Note that the password hash specified for the Ripple server corresponds to the text password used in the CHANGE MASTER TO command. Currently, Ripple does not authenticate based on the usernames and accepts any non-empty username as long as the password matches.
Exploring MySQL Binlog Server - Ripple
It’s possible to monitor and manage the Ripple server using the MySQL protocol from any standard MySQL client. There are a limited set of commands that are supported which you can see directly in the source code on the mysql-ripple GitHub page.
Some of the useful commands are:
SELECT @@global.gtid_executed;
– To see the GTID SET of the Ripple server based on its downloaded binary logs.STOP SLAVE;
– To disconnect the Ripple server from the master.START SLAVE;
– To connect the Ripple server to the master.#cloud #database #developer #high availability #mysql #performance #binary logs #gtid replication #mysql binlog #mysql protocol #mysql ripple #mysql server #parallel threads #proxy server #replication topology #ripple server
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Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community — What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.
The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.
#developers corner #learn transfer learning #machine learning #transfer learning #transfer learning methods #transfer learning resources
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php code for updating data in mysql database. Here, i will show you how to fetch and update data from mysql in php.
https://www.tutsmake.com/php-code-for-update-data-in-mysql-database/
#how to edit data in php using form #how to update data in php using form mysqli #how to fetch and update data from database in php #php code for updating data in mysql database #php #update