Whitney  Durgan

Whitney Durgan

1622538880

Switching Production DB Seamlessly from RDS to Aurora MySQL

How & why we switched our production database to AWS Aurora

Trips Platform is the backend stack that powers the shiny post booking trips experience on Expedia® for both mobile app and website. This system processes all the bookings made on Expedia. As you can imagine, it processes numerous bookings every day. The platform is read & write heavy where reads are more than double the number of writes. We were using 4 Amazon RDS MySQL databases. We ran a spike and found Amazon Aurora to be better suited to our needs in many aspects.

Why Switch to AWS Aurora?

Improved Performance

Amazon Aurora provides 5x the throughput of standard MySQL

Improved Replication

With Aurora, you can provision up to 15 replicas, and replication is performed in milliseconds. By contrast, RDS allows only 5 replicas and the replication process is slower.

High Availability

Amazon Aurora automatically maintains 6 copies of data across 3 Availability Zones (AZs) and will automatically attempt to recover the database in a healthy AZ with no data loss.

These are just a few of the features provided by Aurora. More details can be found here.

#aws #mysql #aurora mysql #rds

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Buddha Community

Switching Production DB Seamlessly from RDS to Aurora MySQL
Whitney  Durgan

Whitney Durgan

1622538880

Switching Production DB Seamlessly from RDS to Aurora MySQL

How & why we switched our production database to AWS Aurora

Trips Platform is the backend stack that powers the shiny post booking trips experience on Expedia® for both mobile app and website. This system processes all the bookings made on Expedia. As you can imagine, it processes numerous bookings every day. The platform is read & write heavy where reads are more than double the number of writes. We were using 4 Amazon RDS MySQL databases. We ran a spike and found Amazon Aurora to be better suited to our needs in many aspects.

Why Switch to AWS Aurora?

Improved Performance

Amazon Aurora provides 5x the throughput of standard MySQL

Improved Replication

With Aurora, you can provision up to 15 replicas, and replication is performed in milliseconds. By contrast, RDS allows only 5 replicas and the replication process is slower.

High Availability

Amazon Aurora automatically maintains 6 copies of data across 3 Availability Zones (AZs) and will automatically attempt to recover the database in a healthy AZ with no data loss.

These are just a few of the features provided by Aurora. More details can be found here.

#aws #mysql #aurora mysql #rds

Joe  Hoppe

Joe Hoppe

1595905879

Best MySQL DigitalOcean Performance – ScaleGrid vs. DigitalOcean Managed Databases

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

2020/06/04時点 Aurora MySQL 5.6 vs 5.7 vs Serverless 機能比較一覧

Aurora MySQLの各エディション×各機能が使える/使えないの一覧表が欲しいなーと思ったので作ってみました。

#aws #mysql #rds #aurora #aurora serverless #serverless

Fredy  Larson

Fredy Larson

1595209620

How to alter tables in production when records are in millions

As a developer, I have experienced changes in app when it is in production and the records have grown up to millions. In this specific case if you want to alter a column using simple migrations that will not work because of the following reasons:

It is not so easy if your production servers are under heavy load and the database tables have 100 million rows. Because such a migration will run for some seconds or even minutes and the database table can be locked for this time period – a no-go on a zero-downtime environment.

In this specific case you can use MySQL’s algorithms: Online DDL operations. That’s how you can do it in Laravel.

First of all create migration. For example I want to modify a column’s name the traditional migration will be:

Schema::table('users', function (Blueprint $table) {
            $table->renameColumn('name', 'first_name');
        });

Run the following command php artisan migrate –pretend this command will not run the migration rather it will print out it’s raw sql:

ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL

Copy that raw sql, remove following code:

Schema::table('users', function (Blueprint $table) {
            $table->renameColumn('name', 'first_name');
        });

Replace it with following in migrations up method:

\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL');

Add desired algorithm, in my case query will look like this:

\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL, ALGORITHM=INPLACE, LOCK=NONE;');

#laravel #mysql #php #alter heavy tables in production laravel #alter table in production laravel #alter tables with million of records in laravel #how to alter heavy table in production laravel #how to alter table in production larave #mysql online ddl operations

Loma  Baumbach

Loma Baumbach

1595781840

Exploring MySQL Binlog Server - Ripple

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.

MySQL Binlog Server Deployment Diagram - ScaleGrid Blog

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.

1. Support for GTID based replication

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.

2. Connecting to the master using replication user and password

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

3. Connection endpoint for the Ripple server

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.

4. Setting up slaves to the Ripple server

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

CLICK TO TWEET

5. Ripple server management

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