Determining the best and most suitable relational database management system (RDBMS) for a given project isn't an easy task and it can be rather challenging at times. It is like benchmarking fast cars created by different racing teams!
The presentation will compare, using a large body of experimental results, two highly-available cloud closed-source products, Amazon Aurora MySQL and RDS MySQL, both based on the Open Source MySQL Edition.
Both use cases have demonstrated that MySQL is a great
solution for concurrent writes, reads and read and write traffic.
Additionally, both scenarios have proven to be successful, satisfying data integrity, reliability and scalability with different outcomes.
The role of the DBA is evolving, as more companies and products move to a hybrid model where, along with their traditional work, DBAs are expected to code. We've scaled our Data Stores team to bring in pure developers, pure DBAs, and a mix of both. We were able to find creative ways to help support our DBAs to better adapt to the changes in the industry. We're discovering how increasingly complex it is to find candidates with this mix of experience, and through learning from our struggles we have learned the best methods to find DBAs and to help them evolve. We want DBAs to be prepared for this new world and would love to share our industry findings with this community.
One of the most popular new features of MySQL 5.7 was JSON support. Now you can use SQL to search, extract information from, and change JSON documents. MySQL 8.0 takes this a step further. Using the JSON_TABLE function, you will be able to construct relational tables based on the contents of JSON documents. This way, you will be able to use the power of SQL to process JSON. For example, you can use SQL aggregate functions on your JSON data, or use the WHERE clause to find interesting objects within a JSON array.
This lightning talk will give a short introduction into how JSON_TABLE provides the missing link when processing JSON documents in MySQL.
Scaling MySQL infrastructure is challenging, traditional setup don't scale horizontally and require manual configuration management.
This talk is about how we scaled MySQL infrastructure at Indeed. Using HaProxy, we dynamically take backends in/out of rotation based on replication lag. Through this proxy, we load-balance reads across a pool of replicas, ensure replication lag is below a threshold, and easily take replicas out of rotation for maintenance, removing the work of manually updating application's configuration.
You will also learn about different routing strategy we use, such as fail-to-primary vs fail-open, and about surprising application connection pool's behaviors we learned along the way.
In master/slave replication cluster, there are many branch nodes. They are full-blown database servers yet its only purpose is to serve binlogs to its slaves.
Blackhole storage engine does not storage any data in the table, but allows the transactions to be recorded in the binlogs. Therefore it is suitable as binlog servers with reduced capacity requirements.
With the release of Percona server 5.7.20-19 in January 2018, MySQL server becomes a viable solution as it fixes two critical bugs related to blackhole engine.
This talk describes the implementation details.
Determining the best and most suitable relational database management system (RDBMS) for a given project isn't an easy task and it can be rather challenging at times. It is like benchmarking fast cars created by different racing teams!
The presentation will compare, using a large body of experimental results, two highly-available cloud closed-source products, Amazon Aurora MySQL and RDS MySQL, both based on the Open Source MySQL Edition.
Both use cases have demonstrated that MySQL is a great
solution for concurrent writes, reads and read and write traffic.
Additionally, both scenarios have proven to be successful, satisfying data integrity, reliability and scalability with different outcomes.
One of the most popular new features of MySQL 5.7 was JSON support. Now you can use SQL to search, extract information from, and change JSON documents. MySQL 8.0 takes this a step further. Using the JSON_TABLE function, you will be able to construct relational tables based on the contents of JSON documents. This way, you will be able to use the power of SQL to process JSON. For example, you can use SQL aggregate functions on your JSON data, or use the WHERE clause to find interesting objects within a JSON array.
This lightning talk will give a short introduction into how JSON_TABLE provides the missing link when processing JSON documents in MySQL.
Scaling MySQL infrastructure is challenging, traditional setup don't scale horizontally and require manual configuration management.
This talk is about how we scaled MySQL infrastructure at Indeed. Using HaProxy, we dynamically take backends in/out of rotation based on replication lag. Through this proxy, we load-balance reads across a pool of replicas, ensure replication lag is below a threshold, and easily take replicas out of rotation for maintenance, removing the work of manually updating application's configuration.
You will also learn about different routing strategy we use, such as fail-to-primary vs fail-open, and about surprising application connection pool's behaviors we learned along the way.
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