The latest from the MySQL community

MySQL is the #1 open source database. Because of MySQL’s highperformance, scalability, and availability, it has been widely popular for Webapplications and has become the foundation for IT platforms that supporthigh-traffic social media portals, e-commerce applications, and fast-growingorganizations. As business models and technology requirements are beingtransformed in all industries, more and more companies are embracing andleveraging the cloud platform to enjoy the benefits of flexibility, agility andcost-savings. Available in Oracle Cloud, the Oracle MySQL Cloud Serviceprovides an enterprise-grade MySQL database service to rapidly, securely, andcost-effectively deliver modern applications. With the latest MySQL 5.7.17 updaterelease, MySQL Group Replication is now available in Oracle MySQL Cloud Serviceand offers native, built-in high availability for MySQL databases.

To gain deeper insight into the benefits and use cases ofMySQL …

MySQL Replication has become an instrumental part of scale-out architectures in LAMP environments. MySQL offers plenty of solutions when there is a need to scale out, the most common being to add read replicas.

Building a database HA stack for production can be daunting. It is not just about setting up replication between a master and some slave servers, it’s also about how to restore broken topologies and fail-over, how applications can keep track of the writable master and the read-only slaves, what to do when servers are corrupted, how to perform backups, and more.

We’ve produced a number of resources aimed at helping users to get started with MySQL Replication or to get more out of their existing setups.

The White Papers The MySQL© Replication Blueprint

This is a great resource for anyone wanting to build or optimise a MySQL replication setup. The MySQL Replication Blueprint is about having a complete …

MySQL Connector/C++ 2.0.4 is the next development milestone of the MySQL

Connector/C++ 2.0 series. Connector/C++ 2.0 can be used to access MySQL
implementing Document Store or in a traditional way, using SQL queries. It
allows writing both C++ applications using X DevAPI or plain C applications
using XAPI.

To learn more about how to write applications using X DevAPI, see X
DevAPI User Guide (http://dev.mysql.com/doc/x-devapi-userguide/en/) and X
DevAPI reference at
https://dev.mysql.com/doc/dev/connector-cpp/devapi_ref.html. For more
information about using plain C XAPI see XAPI reference at
…

In this blog, we’ll look at running Percona XtraBackup on Windows via a Docker container.

The question whether Percona XtraBackup is available for Windows comes up every so often. While we are not planning to provide regular releases for Windows, I decided to share a way to run Percona XtraBackup in a Docker container (especially since Docker support for Windows has become more and more stable).

For this exercise, I created a playground Docker image: perconalab/percona-xtrabackup.

First, we need to prepare a few things to make it work:

1. Install Docker on Windows (the current version I am running is 17.03)
2. Enable the sharing of disk C in Docker settings
3. Find out the IP address MySQL is running on …

In this blog post, we’ll look at how Prophet can forecast metrics.

Facebook recently released a forecasting tool called Prophet. Prophet can forecast a particular metric in which we have an interest. It works by fitting time-series data to get a prediction of how that metric will look in the future.

For example, it could be used to:

• Predict how much HTTP traffic we will get, and scale accordingly when needed
• See if a particular feature of our application will have success or if its usage will decline
• Get an approximate date when our database server’s resources will be exhausted
• Forecast new customer’s sign up and resize the staff accordingly
• See what next year’s Black Friday or Cyber Monday will look like, and if we have the resources to handle them
…

MySQL Cluster is a highly available, distributed, shared-nothing database with very interesting performance characteristics for some workloads. Among other features, it supports automatic sharding and allows us to bypass the SQL layer if we don’t need it, via the NDB API (which in my eyes, makes it one of the few transactional nosql databases out there).

In this post, I’ll describe how we can set up replication from MySQL Cluster into a standalone MySQL server using Innodb as the storage engine.

Introduction

There are a few reasons to set up replication between MySQL Cluster and a non-NDB based MySQL server. These reasons include (but are not limited to): the need …

This Log Buffer edition covers Oracle, SQL Server and MySQL blog posts with a touch of Cloud.

Oracle:

Provisioning EBS on Oracle Cloud: Latest Enhancements

ORA-54002 when trying to create Virtual Column using REGEXP_REPLACE on Oracle 12cR2

Business rules, common sense and query performance

Problem with V$RECOVERY_AREA_USAGE view and FRA space not being reclaimed

Updated …

Percona announces the release of Percona XtraDB Cluster 5.7.17-27.20 on March 16, 2017. Binaries are available from the downloads section or our software repositories.

NOTE: You can also run Docker containers from the images in the Docker Hub repository.

Percona XtraDB Cluster 5.7.17-27.20 is now the current release, based on the following:

• …

This blog shares some column store database benchmark results, and compares the query performance of MariaDB ColumnStore v. 1.0.7 (based on InfiniDB), Clickhouse and Apache Spark.

I’ve already written about ClickHouse (Column Store database).

The purpose of the benchmark is to see how these three solutions work on a single big server, with many CPU cores and large amounts of RAM. Both systems are massively parallel (MPP) database systems, so they should use many cores for SELECT queries.

For the benchmarks, I chose …

One of the major challenges of query optimizers is to correctly estimate how many rows qualify from each table of a join. If the estimates are wrong, the optimizer may choose a non-optimal join order.

Before MySQL 5.7, the estimated number of rows from a table only took into account the conditions from the WHERE clause that were used to set up the access method (e.g., the size of an index range scan). This often led to row estimates that were far too high, resulting in very wrong cost estimates for join plans. To improve this issue, MySQL 5.7 introduced a cost model that considered the entire WHERE condition when estimating the number of qualifying rows from each table. This model estimates the filtering effect of the table’s conditions.

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