Running an analytical (OLAP) workload on top of MySQL can be slow and painful. A specifically designed storage format ("Column Store") can significantly improve analytical queries' performance. There are a number of opensource column store databases around. In this talk, I will focus on two of them which can support MySQL protocol: MariaDB ColumnStore and ClickHouse.
I will show some realtime benchmarks and use cases, and demonstrate how MariaDB ColumnStore and ClickHouse can be used for typical OLAP queries. I will also do a quick demo.
MariaDB 10.4 will come with new Galera Replication version 4. This presentation will outline the new features of Galera 4 Replication as present in MariaDB 10.4 and share the early user experiences with it.
Galera is a generic replication plugin, making it possible to deploy synchronous multi-master cluster topologies with database servers supporting Galera Replication plugin API (i.e write set replication, wsrep API) . Currently both MySQL and MariaDB servers have Galera Replication support, and today there are thousands of MySQL and MariaDB based cluster installations, around the world, processing production system loads in bare-metal or cloud deployments.
With Galera 4, MariaDB 10.4 cluster further extends the capabilities of the synchronous Galera replication. The most prominent feature in Galera 4 version, is streaming replication technology, which implements distributed transaction processing within the cluster. With streaming replication, a transaction can be launched to execute in all cluster nodes in parallel. With this, a large transaction can be executed in small fragments due out the transaction life time, and cluster will not choke with the replication of one large transaction write set, as happened in earlier Galera Cluster versions.
Streaming replication works as a foundation for many more features, to be released in short term. e.g. XA transaction support will now be possible thanks to streaming replication technology.
Open source software is not the new kid on the block anymore! But it takes some time and effort to take these independent software components and bundle them into working software that meets your organization's needs. At Walmart Labs, we are having fun automating the full lifecycle of a database using MariaDB in private and public clouds. In this talk, we will go over how we are building a fully automated database platform and the lessons learned from running these distributed systems in a cloud environment at scale.
If you are interested in open source technologies and curious to know how we manage 6000 (and growing!) computes in the cloud with a small team â€“ then come join us for a fun-filled tech talk!
Most Enterprises today own information of critical value such as intellectual property, customers personal data or private financial data. This type of data should never be exposed to unauthorized malicious access.
Our session covers the best security practices for a MariaDB deployment, the latest security related features in the MariaDB Server as well as general information related to potential threats in Enterprise systems and our recommended defense mechanisms.
Subjects covered in this session:
- Potential threats and protection mechanisms
- Secure installation with mysql_secure_installation
- At Rest and in-transit data encryption
* MariaDB TLS support
* Securing client-server communication
* Securing data echange in Replication and Galera Cluster
* Data at Rest and Binlog Encryption
- User Management best practices
* Password validation plugins
* User Account Locking
* Expiration of User Passwords
* Blocking user accounts with --max-password-errors
- External authentication with PAM and Kerberos
- Role-based Access Control
- Monitoring activity using the MariaDB Audit Plugin
When your SQL query reaches the DBMS, it's the optimizer's job to decide how to execute it for you to get the result as fast as possible. To make this decision optimizer can examine the actual table data, but with multi gigabyte and terabyte tables, the only practical solution is to use various data statistics that were collected in advance. The better the statistics and the more precisely it describes the actual data, the faster the plan will be, because the optimizer image of reality will be closer to the actual reality.
In this talk you'll learn what data statistics MariaDB and MySQL can collect, what statements do that, how to tell the optimizer to use it (it won't necessarily do it automatically!) and how it can make your queries many times faster.
And, of course, when not to use indexes, when up-to-date statistics is enough.
There are few ways to take a backup. One of the most used tools is Percona Xtrabackup, MariaBackup, and MySQL Enterprise Backup.
In this talk, the audience will have an in-deep overview of:
- Differences between the tools
- Comparison of features
- Which tool work on which MySQL/MariaDB flavor
- Supported Storage Engines
Make the most of your ColumnStore columnar analytics engine!
Deep dive into best practices for columnar engines in general, what are the best use cases for columnar, and tips and trick for both ColumnStore and other analytics engines.
Analytics without data ingestion
Indexing a no-index engine
How and when to use cross engine joins
Enabling low latency data ingestion
Row+column hybrid approaches
Optimizing data loads
Splitting columns for performance
MySQL and MariaDB have a long list of old, potentially trivial bugs that are annoying if you hit them. No one's really bothered to fix them, so why not you? It doesn't take a large amount of C/C++ knowledge to pick out an old bug, and build/test a MySQL/MariaDB patch to fix an old bug.
I'll talk about what is a sane choice of bug, how to use the existing mtr to help, small test cases, and packaging up and submitting your changes.
But doing this, you'll pay it forwards, for all the positive MySQL/MariaDB experiences you've had.