MySQL Cluster does an automatic sharding/partitioning to the tables across data nodes, enabling databases to scale horizontally to serve read and write-intensive workloads, but what is the default sharding key used in partitioning the data?
According to the recent update (Oct, 2016) of the MySQL Cluster white paper, primary key is the default sharding key:

By default, sharding is based on hashing of the primary key, which generally leads to a more even distribution of data and queries across the cluster than alternative approaches such as range partitioning.

However, that is not the case in all MySQL Cluster versions so far!
In this post, I’ll do some test cases on MySQL Cluster (of 4 datanodes) to confirm the default sharding key.

Testing on MySQL Cluster 7.2.26 …

The innodb_buffer_pool_size the most important variable for entire MySQL server. Last few years, you have seen the drastic improvements in the InnoDB storage engine features. After Oracle acquiring the MySQL, the importance of InnoDB storage engine grows multiple times over MyISAM. Even though MySQL supports multiple pluggable storage engines, one of the main reasons is its ACID compliance properties. Recent improvements in the MySQL 5.7 such as online innodb_buffer_pool_size configuration made it as a highly flexible and allow us to get the best performance without long downtime.
Initially, when I start to configure the innodb_buffer_pool_size variable on my test environment, like most of us, I googled as, 
What is MySQL innodb_buffer_pool_size?Do I need to change MySQL innodb_buffer_pool_size?What are the recommendations for innodb_buffer_pool_size in MySQL?What are the best practices for configuring innodb_buffer_pool_size …

If we work in big application or project of Laravel Framework sometimes we require to manage column value into comma separated because we can save memory of database But if we store comma separated value in column with ids then its difficult to inner join or left join and get records from another

If we work in big application or project of Laravel Framework sometimes we require to manage column value into comma separated because we can save memory of database But if we store comma separated value in column with ids then its difficult to inner join or left join and get records from another

Amazon is releasing new products & services to it’s global cloud compute network at a rate that has all of our heads spinning. Join 32,000 others and follow Sean Hull on twitter @hullsean. Here’s new stuff worth mentioning around databases & data. 1. For ETL – AWS GLUE Moving data from your transactional MySQL or … Continue reading What products & improvements are new on AWS? →

Most users of MySQL utilize the mysqldump utility to backup their database. While mysqldump is handy and easy-to-use (and free), if you have data which is important to your business, then you should take a look at the MySQL Enterprise Edition – and use MySQL Enterprise Backup instead. The MySQL Enterprise Backup allows you to backup your database without the table locking you get with mysqldump. And, it is extremely fast – especially when you have to restore your database. Here is a sample speed comparison between MySQL Enterprise Backup and …

This post discusses archiving MySQL and MongoDB data, and determining what, when and how to archive data.

Many people store infrequently used data. This data is taking up storage space and might make your database slower than it could be. Archiving data can be a huge benefit, both regarding the performance impact and storage savings.

Why archive?

One of the reasons for archiving data is freeing up space on your database volumes. You can store archived data on slower, less expensive storage devices, and current data on the faster database drives. Archiving old data makes backups and restores run faster since they need to process less data. Last, but by no means least, archiving data has the benefit of making your queries perform more efficiently since they do not need to process through old …

This blog compares how PostgreSQL and MySQL handle millions of queries per second.

Anastasia: Can open source databases cope with millions of queries per second? Many open source advocates would answer “yes.” However, assertions aren’t enough for well-grounded proof. That’s why in this blog post, we share the benchmark testing results from Alexander Korotkov (CEO of Development, Postgres Professional) and Sveta Smirnova (Principal Technical Services Engineer, Percona). The comparative research of PostgreSQL 9.6 and MySQL 5.7 performance will be especially valuable for environments with multiple databases.

The idea behind this research is to provide an honest comparison for the two popular RDBMSs. Sveta and Alexander wanted to test the most recent versions of both MySQL and PostgreSQL with the same tool, under the same challenging …

MySQL has had a JSON data type since version 5.7 was released way back in '15. But did you know you could produce JSON output from non-JSON columns? It is very simple and saves a lot of time over trying to format it in your application.

World DatabaseWe will be using the good old World database that MySQL has used for years in documentation, examples, and in the classroom. Starting with a simple query we will build up to something more complex.

SELECT Name, District, Population FROM City;

This will output the data from the table in a tabular format.

'Kabul', 'Kabol', '1780000'
'Qandahar', 'Qandahar', '237500'

Array or Object?We have two options for composing JSON data: JSON_ARRAY and JSON_OBJECT.

Of the two, you will find JSON_ARRAY the least fussy. It will JSON-ize your data very easily. It takes a list of values or an empty list and returns a JSON array.

Why do we sometimes want to keep duplicate indexes?

I’ve done dutiful DBA work in the past to identify and remove what are commonly called duplicate indexes. That is, those indexes that look like (a) and (a,b). The thought is that a query will utilize an index as easily on (a) as on (a,b), and removing (a) will save storage cost and write performance. I’ve had the experience, though, of removing (a) and seeing performance tank.

(As an aside, these are really redundant indexes. A duplicate index would be (a,b) and (a,b) by two different names – this can commonly be done by object relational mapping (ORM) or other automated schema creation tools. I’ll call (a) and (a,b) redundant indexes below.)

This test is on Percona Server 5.7.14 with the sys schema installed and performance schema enabled.

Given two tables with the same number of rows and …