Today, we officially announced the fact that Blackbird.io has been acquired by Pythian. I first met its founder, Paul Vallee, in 2007. Paul reached out to me about joining Pythian to found a San Francisco presence. At the time, I was one year into PalominoDB, and was having such a good time being my own boss and building a business that I politely declined. Since then, Paul and I have caught up at PerconaLive (O’Reilly’s MySQL conf for you old schoolers) regularly - using the time to catch up, share successes (and failures), and discuss the marketplace at large. We’ve also competed, healthily and as good sports.
Over those 6 years since that first contact, I’ve also fallen in love with the world of open-source data, both big and small. I’ve enjoyed working on the IOUG mysql conference, presenting at Percona Live, Kaleidoscope, Velocity and more. I’ve really enjoyed meeting and building great collegial relationships with people from Pythian, from Percona, from SkySQL/MariaDB, SeveralNines, Codership, Mozilla and from so many MySQL shops, big and small.
About 2 years ago, I realized the company had really gone to the level when we began working with the Obama for America campaign, followed immediately by one of the largest online games in the industry (which DriveDev brought in). It was that time that I had really begun to fully embrace the future of cloud computing, database as a service, and the culture of DevOps that could harness automation, orchestration, continuous delivery and so much more to drive unparalleled value to our clients; not to mention making our lives as DBAs so much easier.
The last 6 months as Blackbird.io has truly been a whirlwind. Having one’s team go from 25 to 55 pushed me as a leader and executive in ways I didn’t anticipate. I’ve had some truly magical moments, and some spectacular ball drops. Greatest of all, I’ve seen what I consider to be the future of IT service delivery converge with the world of databases, which is truly my passion.
So, after this year’s PerconaLive, when Paul and I sat down to discuss DevOps, the future of service organizations and the status of the ecosystem, that previous offer began to percolate. It was also around this time we began to realize that the opportunity ahead of us was huge, and the time to take market share was limited. Thus, I reached out to Paul. In two months, my co-founders, Aaron Lee and Vicki Vance, and the full executive team at Pythian pushed through a business transaction that has truly been massive. I can already see a great fit in culture, in drive, in passion and in work ethic. The excitement and pride I feel right now in what has come of the work of three companies, 4 founders and a team of over 300 is unparalleled.
Thank you Blackbird, every one of you! And thank you Pythian. Here’s to a very exciting road ahead.

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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