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Displaying posts with tag: cluster (reset)

NoSQL Java API for MySQL Cluster: Questions & Answers
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The MySQL Cluster engineering team recently ran a live webinar, available now on-demand (http://www.mysql.com/news-and-events/on-demand-webinars/display-od-716.html) demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster (http://www.mysql.com/products/cluster/), and how these can be used in building real-time, high scale Java-based services that require continuous availability.

Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs.

First, a little bit about why we developed these APIs and why they are interesting to Java developers.

ClusterJ and Cluster JPA

ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used

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ARM based data center. Inspiring.
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In a previous post I wrote ARM based servers. Since then, and thanks to all the comments and responses I got, I looked more into this ARM thing and it's absolutely fascinating...

Look at this beauty (taken from the site of Calxeda, the manufacturer):

What is it? A chip? A server? No, it's a cluster of 4 servers...

And this:







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The catch-22 of read/write splitting
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In my previous post I covered the shard-disk paradigm's pros and cons, but the conclusion that is that it cannot really qualify as a scale-out solution, when it comes to massive OLTP, big-data, big-sessions-count and mixture of reads and writes.

Read/Write splitting is achieved when numerous replicated database servers are used for reads. This way the system can scale to cope with increase in concurrent load. This solution qualifies as a scale-out solution as it allow expansion beyond the boundaries of one DB, DB machines are shared-nothing, can be added as a slave to the replication "group" when required.



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New MySQL & MariaDB Instructional Videos from SkySQL
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Are you looking to expand your knowledge about MySQL and MariaDB database solutions?

Well, you’re in luck! SkySQL is introducing an exclusive collection of educational videos featuring some of the industry’s leading experts on the MySQL database and related technologies. View informative, technical talks on a variety of topics, from the experts at SkySQL, MariaDB, Calpont InfiniDB, Continuent, ScaleDB, Severalnines, Sphinx, Webyog, and others.

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Why shared-storage DB clusters don't scale
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Yesterday I was asked by a customer for the reason why he had failed to achieve scale with a state-of-the-art "shared-storage" cluster. "It's a scale-out to 4 servers, but with a shared disk. And I got, after tons of work and efforts, 130% throughput, not even close to the expected 400%" he said.

Well, scale-out cannot be achieved with a shared storage and the word "shared" is the key. Scale-out is done with absolutely nothing shared or a "shared-nothing" architecture. This what makes it linear and unlimited. Any shared resource, creates a tremendous burden on each and every database server in the cluster.

In a previous post, I identified database engine activities such as buffer management, locking, thread locks/semaphores,



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MySQL Cluster on Raspberry Pi
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Earlier this week, Andrew Morgan wrote a piece on running MySQL Cluster on Raspberry Pi. Since the term “Cluster” is hideously overloaded, I’ll note that we’re talking about the NDB cluster storage engine here, a very specific architecture originally acquired by MySQL AB from Ericsson (telco).

Raspberry Pi is a new single-board computer based on the ARM processor series (same stuff that powers most mobile phones these days), and it can run Linux without any fuss. Interfaces include Ethernet, USB, and HDMI video, and the cost is $25-50. I’m looking

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Dynarr256 for DBACC -or- The death of MAX_ROWS
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Back in 2006 we became aware of problems storing large numbers of rows in a single table in cluster. Johan Andersson and Yves Trudeau have each blogged about the problem and the common workaround here and here.  We've since then done some cleanup to provide a more proper "Table is full" error message when running into this problem.

As explained in the referenced blog posts, the problem is the result of a limitation on the size of the hash index of each partition. The hash index for each partition would allow at most ~49 million records. By default an ndbd or ndbmtd node have only 1 local query handler (LQH) block and thus 1 partition per node.  The ndbmtd nodes having

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MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!
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Summary (aka TL/DR):

Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster

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A small rant on Galera & XtraDB Cluster
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I had to install Percona XtraDB Cluster, I think for the first time since it was announced stable. I remembered many problems I faced with beta releases, which was understandable given they were only for a preview, but this time I hoped for significant improvements.

I have to say I am generally quite sensitive about simple problems that could/should be easily discovered and corrected. Well, it didn’t take five minutes to see a few of such problems. These minutes I spent installing the database binaries from Percona Yum repository. It turned out that was enough to see a lot of errors for no reason. Not a good thing.

[..]
  Installing : 1:Percona-XtraDB-Cluster-server-5.5.23-23.5.333.rhel6.x86_64         5/5
ls: cannot access /var/lib/mysql/*.err: No such file or directory
ls: cannot access /var/lib/mysql/*.err: No such file or directory
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Configuring MySQL Cluster Data Nodes
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In my previous blog post, I discussed the enhanced performance and scalability delivered by extensions to the multi-threaded data

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MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1
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Summary

The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 (http://mysql.com/products/cluster/) to deliver over 8x higher

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Performance Testing of MySQL Cluster: The flexAsynch Benchmark
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Following the release of MySQL Cluster 7.2 (http://mysql.com/products/cluster/), the Engineering has been busy publishing a range of new performance benchmarks

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Guide to MySQL & NoSQL, Webinar Q&A
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Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and

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The CAP theorem and MySQL Cluster
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tldr; A single MySQL Cluster prioritises Consistency in Network partition events. Asynchronously replicating MySQL Clusters prioritise Availability in Network partition events.


I was recently asked about the relationship between MySQL Cluster and the CAP theorem. The CAP theorem is often described as a pick two out of three problem, such as choosing from good, cheap, fast. You can have any two, but you can't have all three. For CAP the three qualities are 'Consistency', 'Availability' and 'Partition tolerance'. CAP states that in a system with data replicated over a network only two of these three qualities can be maintained at once, so which two does MySQL Cluster provide?

Standard 'my interpretation of CAP' section

Everyone who discusses CAP like to rehash





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Where Would I Use MySQL Cluster?
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One billion
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As always, I am a little late, but I want to jump on the bandwagon and mention the recent MySQL Cluster milestone of passing 1 billion queries per minute. Apart from echoing the arbitrarily large ransom demand of Dr Evil, what does this mean?

Obviously 1 billion is only of interest to us humans as we generally happen to have 10 fingers, and seem to name multiples in steps of 10^3 for some reason. Each processor involved in this benchmark is clocked at several billion cycles per second, so a single billion is not so vast or fast.

Measuring over a minute also feels unnatural for a computer performance benchmark - we are used to lots of things happening every second! A minute is a long time in silicon.

What's





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Surprises in store with ndb_restore
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While doing some routine fiddling regarding some topic I've now forgotten, I discovered that ndb_restore was doing something quite surprising. It's been common wisdom for some time that one can use ndb_restore -m to restore metadata into a new cluster and automatically have your data re-partitioned across the data nodes in the destination cluster. In fact, this was the recommended procedure for adding nodes to a cluster before online add node came along. Since MySQL Cluster 7.0, though, ndb_restore hasn't behaved that way, though that change in behavior doesn't seem to be documented and most don't know that the change ever took place.

I'll go through some of the methods you can use to find information about the partitioning strategy for an NDB table, talk a bit about why ndb_restore stopped working the way most everyone expected

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MySQL Cluster 7.2 GA Released, Delivers 1 BILLION Queries per Minute
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70x Higher JOIN Performance, NoSQL Key-Value API & Cross Data Center Sharding with Synchronous Replication 

0 0 1 535 3052 Homework 25 7 3580 14.0 Normal 0 false  [Read more...]
Announcing SkySQL™ Enterprise HA for the MariaDB® & MySQL® databases
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SkySQL™ today announced the immediate availability of SkySQL™ Enterprise HA, its leading 360° degrees High Availability solution for the MySQL® & MariaDB® databases.

High Availability is the #1 requested enhancement to the MySQL & MariaDB servers, even more popular than scalability and performance.  And with SkySQL's expertise at hand, it is now easier than ever before for customers to achieve the level of High Availability that they want.

SkySQL™

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2011, A great year for MySQL in review...
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I see so many posts on what happened to company X, product Y and dream Z that I couldn't resist the temptation to summarize this great year for MySQL. At the end of 2010, Oracle did an announcement we were all waiting for: MySQL 5.5 is GA! Another year has passed since then and it's time to reflect on what has been done.

I know this is a long post. I tried to rewrite it at least 10 times to make it shorter, but I couldn't condense the list. Hence, I wrote a summary in the beginning for those who don't want to read it all.

I believe that 2011 was an exceptional year for MySQL and I really enjoy being part of this team. I wish all of us a lot of success and fun in the years to come!

Summary:







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Eventual Consistency in MySQL Cluster - implementation part 3
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As promised, this is the final post in a series looking at eventual consistency with MySQL Cluster asynchronous replication. This time I'll describe the transaction dependency tracking used with NDB$EPOCH_TRANS and review some of the implementation properties.

Transaction based conflict handling with NDB$EPOCH_TRANS

NDB$EPOCH_TRANS is almost exactly the same as NDB$EPOCH, except that when a conflict is detected on a row, the whole user transaction which made the conflicting row change is marked as conflicting, along with any dependent transactions. All of these rejected row operations are then handled using






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Eventual consistency in MySQL Cluster - implementation part 2
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In previous posts I described how row conflicts are detected using epochs. In this post I describe how they are handled.

Row based conflict handling with NDB$EPOCH

Once a row conflict is detected, as well as rejecting the row change, row based conflict handling in the Slave will :
  • Increment conflict counters
  • Optionally insert a row into an exceptions table
For NDB$EPOCH, conflict detection and handling operates on one Cluster in an Active-Active pair designated as the Primary. When a Slave MySQLD attached to the Primary Cluster detects a conflict between data stored in the








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Using MySQL Cluster to Protect & Scale the HDFS Namenode
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The MySQL Cluster (http://mysql.com/products/cluster/) product team is always interested to see new and innovative uses of the database. Last week, a team of students at the KTH Royal Institute

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Using MySQL Cluster to Protect & Scale the HDFS Namenode
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The MySQL Cluster (http://mysql.com/products/cluster/) product team is always interested to see new and innovative uses of the database. Last week, a team of students at the KTH Royal Institute

  [Read more...]
Eventual consistency in MySQL Cluster - implementation part 1
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The last post described MySQL Cluster epochs and why they provide a good basis for conflict detection, with a few enhancements required. This post describes the enhancements.

The following four mechanisms are required to implement conflict detection via epochs :
  • Slaves should 'reflect' information about replicated epochs they have applied
    Applied epoch numbers should be included in the Slave Binlog events returning to the originating cluster, in a Binlog position corresponding to the commit time of the






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    Eventual Consistency in MySQL Cluster - using epochs
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    Before getting to the details of how eventual consistency is implemented, we need to look at epochs. Ndb Cluster maintains an internal distributed logical clock known as the epoch, represented as a 64 bit number. This epoch serves a number of internal functions, and is atomically advanced across all data nodes.

    Epochs and consistent distributed state

    Ndb is a parallel database, with multiple internal transaction coordinator components starting, executing and committing transactions against rows stored in different data nodes. Concurrent transactions only interact where they attempt to lock the same row. This






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    Speaking at Oracle UK User Group conference
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    I will be speaking in the MySQL track of the UK Oracle User Group conference on 5th December in Birmingham UK. The title of the session is "Building Highly Available and Scalable, Real Time Services with MySQL Cluster" - full details here.

    I'm not a regular conference attendee, never mind speaker. However I'm looking forward to meeting current and potential MySQL users, and also attending some of the talks in the MySQL and other tracks. Maybe I can learn something about RAC, or Exadata?

    If you are attending and want




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    Clustering MySQL instances with Oracle Clusterware 11gR2
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    I've been doing lately quite many database clustering implementations; Oracle RAC and since we have many MySQL instances in production, had to find a good way to make MySQL instances highly available also.

    One good solution for this is managing MySQL instances with clusterware and since we are planning to use Oracle RAC on Oracle Enterprise Linux anyway, then Oracle Clusterware is an excellent candidate for this task. Also... Oracle Clusterware is included with Oracle Enterprise Linux at no additional charge.

    Requirements I had:

    • Multiple MySQL instances running in the same cluster, in case of node failure affected MySQL instances are moved to any other surviving node (least loaded)
    • Different MySQL instances may run
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    MySQL Cluster, and NoSQL
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    Those are the topics we cover in the latest episode of our “Meet The MySQL Experts” podcast.

    Mat Keep and Bernd Ocklin talk about new database requirements, and walk us through what's new in the second Development Milestone Release of MySQL Cluster 7.2, including impressive performance improvements, new NoSQL access via memcached, cross data center scalability, and more...

    Enjoy the podcast!

    MySQL Cluster, and NoSQL
    Employee_Team +1 Vote Up -0Vote Down

    Those are the topics we cover in the latest episode of our “Meet The MySQL Experts” podcast.

    Mat Keep and Bernd Ocklin talk about new database requirements, and walk us through what's new in the second Development Milestone Release of MySQL Cluster 7.2, including impressive performance improvements, new NoSQL access via memcached, cross data center scalability, and more...

    Enjoy the podcast!

    Previous 30 Newer Entries Showing entries 61 to 90 of 244 Next 30 Older Entries

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