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Showing entries 1 to 10 of 19 9 Older Entries

Displaying posts with tag: oltp (reset)

Using Lua-enabled sysbench
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A quite common benchmark for MySQL is sysbench. It was written nearly 10 years ago by Alexey Kopytov.

Sysbench has modes to benchmark raw CPU performance, mutex speed, scheduler overhead and file IO performance. The probably most often used sysbench mode is OLTP. This benchmark mimics a OLTP scenario with small transactions hitting an optimized database. There are many variables to play with, most important is the number of simulated application threads (option --num-threads). The OLTP benchmark can be run read-only, then it does 14 SELECT queries per transaction. Or it can be run read-write …

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Scale Up, Partitioning, Scale Out
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On the 8/16 I conducted a webinar titled: "Scale Up vs. Scale Out" (http://www.slideshare.net/ScaleBase/scalebase-webinar-816-scaleup-vs-scaleout):


ScaleBase Webinar 8.16: ScaleUp vs. ScaleOut from ScaleBase
The webinar was successful, we had many attendees and great participation in …



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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... …



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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 …

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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 …

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Scale-out your DB on ARM-based servers
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Today, I think we witnessed a small sign for a big revolution...

http://www.pcworld.com/businesscenter/article/256383/dell_reaches_for_the_cloud_with_new_prototype_arm_server.html
"Dell announced a prototype low-power server with ARM processors, following a growing demand by Web companies for custom-built servers that can scale performance while reducing financial overhead on data centers"In short, ARM (see Wikipedia definition …


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Scale differences between OLTP and Analytics
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In my previous post,http://database-scalability.blogspot.com/2012/05/oltp-vs-analytics.html, I reviewed the differences between OLTP and Analytics databases.

Scale challenges are different between those 2 worlds of databases.



Scale challenges in the Analytics world are with the growing amounts of data. Most solutions have been leveraging those 3 main …






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The CAP Theorem Event Horizon
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The CAP Theorem has become a convenient excuse for throwing data consistency under the bus. It is automatically assumed that every distributed system falls prey to CAP and therefore must sacrifice one of the three objectives, with consistency being the consistent fall guy. This automatic assumption is simply false. I am not debating the validity of the CAP Theorem, but instead positing that the onset of CAP limitations—what I call the CAP event horizon—does not start as soon as you move to a second master database node. Certain approaches can, in fact, extend the CAP event horizon.
Physics tells us that different properties apply at different scales. …

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HP Needs a Linux OLTP Database...FAST
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Oracle, after dating HP, Dell, Netapp and EMC has found its mate in Sun. Oracle is now becoming a systems company, and unceremoniously dumping these former paramours. These leaves the spurned lovers to find alternate accommodations, especially in the area of the database.

As I have stated previously on this blog, the clear partner of choice on the Windows front is Microsoft. This is demonstrated by today’s …

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Settingup DBT-2
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DBT-2 is a TPC-C like OLTP benchmark, and very popular amongst many MySQL users. It is used by MySQL QA team to test the stability and performance before release. However, steps to setup DBT-2 is a little bit messy, and its README files include some dummy information. So I introduce you these steps below:

1. Download it!

You can download the source code from here: http://osdldbt.sourceforge.net/

2. Required packages

The following perl packages are required to build DBT-2. Unfortunately, configure script doesn't complain even if they are …







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Showing entries 1 to 10 of 19 9 Older Entries

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