Search Results for: big data load

Importing big tables with large indexes with Myloader MySQL tool

Mydumper is known as the faster (much faster) mysqldump alternative. So, if you take a logical backup you will choose Mydumper instead of mysqldump. But what about the restore? Well, who needs to restore a logical backup? It takes ages! Even with Myloader. But this could change just a bit if we are able to take […]

Facebook MySQL database engineers ready for Percona Live London 2014

With 1.28 billion active users, Facebook MySQL database engineers are active and extremely valuable contributors to the global MySQL community. So naturally they are also active participants of Percona Live MySQL conferences! And next week’s Percona Live London 2014 (Nov. 3-4) is no exception. (Register now and use the promotional code “Facebook” to save £30!) […]

Rackspace doubling-down on open-source databases, Percona Server

Founded in 1998, Rackspace has evolved over the years to address the way customers are using data – and more specifically, databases. The San Antonio-based company is fueling the adoption of cloud computing among organizations large and small. Today Rackspace is doubling down on open source database technologies. Why? Because that’s where the industry is […]

MySQL & OpenStack: How to overcome issues as your dataset grows

MySQL is the database of choice for most OpenStack components (Ceilometer is a notable exception). If you start with a small deployment, it will probably run like a charm. But as soon as the dataset grows, you will suddenly face several challenges. We will write a series of blog posts explaining the issues you may […]

How to scale big data applications using MySQL sharding frameworks

This Wednesday I’ll be discussing two common types of big data: machine-generated data and user-generated content. These types of big data are amenable to sharding, a commonly used technique for spreading data over more than one database server. I’ll be discussing this in-depth during a live webinar at 10 a.m. Pacific time on Sept. 24. […]

Managing big data? Say ‘hello’ to HP Vertica

Over the past few months, I’ve seen an increase in the following use case while working on performance and schema review engagements: I need to store exponentially increasing amounts of data and analyze all of it in real-time. This is also known simply as: “We have big data.” Typically, this data is used for user […]

A closer look at the MySQL ibdata1 disk space issue and big tables

A recurring and very common customer issue seen here at the Percona Support team involves how to make the ibdata1 file “shrink” within MySQL. I can only imagine there’s a degree of regret by some of the InnoDB architects on their design decisions regarding disk-space management by the shared tablespace* because this has been a big […]

Sysbench Benchmarking of Tesora’s Database Virtualization Engine

Tesora, previously called Parelastic, asked Percona to do a sysbench benchmark evaluation of its Database Virtualization Engine on specific architectures on Amazon EC2. The focus of Tesora is to provide a scalable Database As A Service platform for OpenStack. The Database Virtualization Engine (DVE) plays a part in this as it aims at allowing databases […]

Using InfiniDB MySQL server with Hadoop cluster for data analytics

In my previous post about Hadoop and Impala I benchmarked performance of analytical queries in Impala. This time I’ve tried InfiniDB for Hadoop (open-source version) on the modern hardware with an 8-node Hadoop cluster. One of the main advantages (at least for me) of InifiniDB for Hadoop is that it stores the data inside the Hadoop cluster but uses the […]

How to improve InnoDB performance by 55% for write-bound loads

During April’s Percona Live MySQL Conference and Expo 2014, I attended a talk on MySQL 5.7 performance an scalability given by Dimitri Kravtchuk, the Oracle MySQL benchmark specialist. He mentioned at some point that the InnoDB double write buffer was a real performance killer. For the ones that don’t know what the innodb double write […]