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MySQL Cluster Overview
MySQL Cluster is a technology that enables clustering of in-memory databases in a shared-nothing system. The shared-nothing architecture enables the system to work with very inexpensive hardware, and with a minimum of specific requirements for hardware or software. MySQL Cluster is designed not to have any single point of failure. In a shared-nothing system, each component is expected to have its…
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2012, the Best Year for MySQL (...so far, but more to come)
It's the end of the year and, before the world ends ;-) , I feel the pressure to follow up on last year's article "2011, a great year for MySQL in Review". I'll adopt a similar format and mention things in context, covering products, marketing, momentum, etc. at a high level. I may have missed something and I hope my colleagues will contribute to the list. I really do think it's been the best year for MySQL so far... well, at least since when I signed my contract with MySQL AB at the end of 2007. We're just at the beginning of our journey and I wish to the MySQL family, to our community and ecosystem an even better 2013! Summary With MySQL Cluster 7.2 GA, MySQL 5.6 Release Candidate and Cluster 7.3 DMR this is the start of something exceptional. These products are introducing long-awaited features and received very positive feedback from our community. New windows tools joined the party to help customers migrate from Microsoft SQL Server and access MySQL from Excel. MySQL Cluster Manager has been updated and the new auto-installer saw the light of the day. We improved our Connectors, released new ones and delivered additional value to MySQL Enterprise Edition customers. We've also held our first ever MySQL Connect conference that's been a phenomenal success and the MySQL momentum is growing exponentially. Products MySQL 5.6 will be loved by developers, giving them more freedom to build next generation applications. With huge performance improvements, new NoSQL access and better replication, that's going to be the best MySQL release to date. New options for High Availability are waiting to be deployed in your data centers to increase service levels and policy-based auditing will make your servers safer. MySQL Cluster 7.2 went GA in February, initially delivering 1.2 Billion queries per minute, but then beating his own achievement and producing 1.1 Billion queries writes per minute. Adaptive Query Localization and better ease of use increased Cluster use cases. Leveraging our Not-Only SQL strategy, the latest previews introduced Node.JS access to provide developers further flexibility. Last but not least, Foreign Keys are now part of MySQL Cluster 7.3 DMR. Case Studies A lot of case studies can be found here, but let me pick some of the recent noteworthy ones:
MySQL Cluster Powers El Chavo from Playful Play, Latin America's Most Popular Facebook Game.
RedeHost Quadriples Backup Speed with MySQL Enterprise Edition
With Its MySQL Database-as-a-Service CERN Empowers Scientists
StayFriends Secures a Leading Position Among European Social Media Sites with Robust, High-Performance, Relational Database
Tilgin Improves Subscriber Device Management by Enabling Telecommunications Operators with Robust Database Solution
Verizon Wireless Supports its Mission-Critical Employee Portal with MySQL
A special mention goes to Twitter, who's handled a huge workload with MySQL during 2012 Presidential Elections
Events & Momentum At the first ever MySQL Connect conference, Edward Screven presented enlightening statistics:
Over 15 Million Estimated Active Installations
Facebook: 163k Fans, +35% Yoy Growth
Twitter: 25k Followers, +67% Yoy Growth
MySQL Newsletter: 1,4m Subscribers, +20% YoY Growth
Events: Dozens Of Fully Booked Dev Days & Tech Tours
Awards: CRN, Linux Journal, PHP Architect...
Several of those numbers have grown since then, and MySQL once again got awarded the Linux Journal Reader’s Choice Award as Best Database for 2012. People are downloading, tweeting, liking, adopting and blogging about MySQL at a great pace. Embedding MySQL has become a common practice. Adoption in the Cloud is skyrocketing and MySQL has emerged as the leading database, offered by the vast majority of cloud services providers. MySQL is also a key component of big data platforms, with Hadoop vendors estimating 80% of their deployments are integrated with MySQL. MySQL is everywhere! To all MySQL users, customers, partners, colleagues, developers, advocates and aficionados: Thank you for another amazing year! Go MySQL!
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MySQL Cluster Casual Talks
On last Thursday, I attended the event. It was first time for me to attend the event related MySQL. The atmosphere was casual and relax but the contents were interesting and helpful.
Let me share my feedback here.
By the way, at this time the details mainly refer to the version 7.3.
Full ACID properties support
No SPOF, good for DR because it can be composed of nodes across data centers and so on, they mentioned and emphasized some good points of it.
But just for me the full ACID support can be the key feature as a distributed product. for MySQL guys it seems natural thing but I think MySQL Cluster can stress the ACID support more if compared to other distributed system.
Strict limitation of the scale out
An expert said, MySQL Cluster can have 48 nodes as the SQL node and also 256 as the data node at the most.
I was surprised with the strict number. as far as I know all the other distributed system doesn't have such a concrete number of limitation. I'd like to check the reason of it later.
Notes from experience with MySQL Cluster for 4 years
Another expert gave presentation based on his experience. It was very informative for me. That kind of topics will never be written in the white paper.
If GCP (Global Check Point) stops, your system severely damaged. Adjust the threshold for it.
Data node rolling restart is enable, but if you do it without service out, you must consider a plan for coincident errors during the restart in advance.
Hard to locate bottleneck. It seems to me that any distributed system requires monitoring system to be maintained.
Take care of data life cycle. For instance, if 'DELETE' data to make spare memory space without restating the data node, the spare will reuse only for the same table.
NDB has online backup function, but recovery data with it will be very slow.
QA
An attendee asked some questions. One of them is very interesting for me.
Q. How can we design data schema for NDB storage engine ? Or can we reuse data schema for InnoDB to it ?
A. There’s only one way to find out. :p
Not a silver bullet
Anyway, there is no silver bullet. Just demonstrate it and go for yourself!
My impression
Before decide to go with MySQL Cluster, do consider MySQL.
At the last, I'd like to thank all the community member involved and GMO guys. I had good time in the event. Thanks so much !
Put together by the team at Altoros Systems Inc., this time run in the Amazon EC2 and including Cassandra, HBase, MongoDB, MySQL Cluster, sharded MySQL and Riak:
After some of the results had been presented to the public, some observers said MongoDB should not be compared to other NoSQL databases because it is more targeted at working with memory directly. We certainly understand this, but the aim of this investigation is to determine the best use cases for different NoSQL products. Therefore, the databases were tested under the same conditions, regardless of their specifics.
Teaser: HBase got the best results in most of the benchmarks (with flush turned off though). And I’m not sure the setup included the latest HBase read improvements from Facebook.
Original title and link: YCSB Benchmark Results for Cassandra, HBase, MongoDB, MySQL Cluster, and Riak (NoSQL database©myNoSQL)
Given the following Hadoop NameNode problem:
the problem is, if the Namenode crashes, the entire file system becomes inoperable because clients and Datanodes still need the metadata to do anything useful. Furthermore, since the Namenode maintains all the metadata only in memory, the number of files you can store on the filesystem is directly proportional to the amount of RAM the Namenode has. As if that’s not enough, the Namenode will be completely saturated under write intensive workloads, and will be unable to respond to even simple client side queries like ls. Have a look at Shvachko’s paper which describes these problems at great length and depth, on which we’ve based our work.
Lalith Suresh has worked for the last couple of months on the following solution:
“Move all of the Namenode’s metadata storage into an in-memory, replicated, share-nothing distributed database.”
[…] We chose MySQL Cluster as our database because of its wide spread use and stability. So for the filesystem to scale to a larger number of files, one needs to add more MySQL Cluster Datanodes, thus moving the bottleneck from the Namenode’s RAM to the DB’s storage capacity. For the filesystem to handle heavier workloads, one needs to add only more Namenode machines and divide the load amongst them. Another interesting aspect is that if a single Namenode machine has to reboot, it needn’t fetch any state into memory and will be ready for action within a few seconds (although it still has to sync with Datanodes). Another advantage of our design is that the modifications will not affect the clients or Datanodes in anyway, except that we might need to find a way to divide the load among the Namenodes.
His post covers the how, but also pros and cons of his solution. And the result is available on GitHub.
Update: Hortonworks is already working on a the next generation of Apache Hadoop MapReduce which is focusing on reliability, availability, scalability, and predictable latency. But this doesn’t make Lalith’s work less interesting .
Original title and link: MySQL Cluster Used to Implement a Highly Available and Scalable Hadoop NodeName (NoSQL database©myNoSQL)
MySQL Sharding vs MySQL Cluster
StackExchange Q&A:
Q: Considering performance only, can a MySQL Cluster beat a custom data sharding MySQL solution?
A: I would say that MySQL Cluster could achieve higher throughput/host than sharded MySQL+InnoDB provided that :
Queries are simple
All data fits in-memory
In terms of latency, MySQL Cluster should have more stable latency than sharded MySQL. Actual latencies for purely in-memory data could be similar. As queries become more complex, and data is stored on disk, the performance comparison becomes more confusing.
Make sure you read the complete answer as it covers some more MySQL Sharding vs MySQL Cluster pros and cons.
Mat Keep
Original title and link: MySQL Sharding vs MySQL Cluster (NoSQL database©myNoSQL)
Podcast: MySQL Cluster News: Performance Improvements,New NoSQL Access
Mat Keep and Bernd Ocklin discuss what’s new in the second milesone release of MySQL Cluster 7.2: performance improvements, new NoSQL access (memcached protocol), cross data center scalability. Download the mp3.
Original title and link: Podcast: MySQL Cluster News: Performance Improvements,New NoSQL Access (NoSQL database©myNoSQL)
