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Showing entries 1 to 10 of 222 10 Older Entries

Displaying posts with tag: Benchmarks (reset)

Generating test data from the mysql> prompt
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There are a lot of tools that generate test data.  Many of them have complex XML scripts or GUI interfaces that let you identify characteristics about the data. For testing query performance and many other applications, however, a simple quick and dirty data generator which can be constructed at the MySQL command line is useful.

First, let’s talk about what kind of data you can easily create with MySQL function calls:

You can generate a decimal number between zero and another number using the MySQL RAND() function like the following query (here between 0 and 10000):

SELECT RAND() * 10000;

Similarly, you can generate a random integer by adding the FLOOR() function:

SELECT FLOOR(RAND() * 10000)

You can generate a random string of 32 characters using MD5():

SELECT MD5(RAND() * 10000)

You can

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Using sysbench 0.5 for performing MySQL benchmarks
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Given the recent excitement & interest around OpenStack I wanted to make sure I was ready to conduct appropriate evaluations of system performance.  I generally turn to sysbench since it comes with a variety of different tests (accessed via –test= option interface), including:

  • fileio – File I/O test
  • cpu – CPU performance test
  • memory – Memory functions speed test
  • threads – Threads subsystem performance test
  • mutex – Mutex performance test

As you can see, sysbench lets you stress many of the fundamental components of your hardware and infrastructure, such as your disk subsystem, along with your CPUs and memory. An additional option exists that is designed to perform synthetic stress testing of MySQL, and I was surprised when I didn’t see it in the

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A closer look at the MySQL ibdata1 disk space issue and big tables
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A recurring and very common customer issue seen here at the Percona Support team involves how to make the ibdata1 file “shrink” within MySQL. I can only imagine there’s a degree of regret by some of the InnoDB architects on their design decisions regarding disk-space management by the shared tablespace* because this has been a big frustration for many MySQL users over the years.

There’s a very old bug (“InnoDB ibdata1 never shrinks after data is removed,” Sept. 8 2003) documenting user dissatisfaction. Shortly before that issue celebrated its 10th anniversary, James Day, MySQL senior principal support engineer at Oracle, posted a comment

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A closer look at the MySQL ibdata1 disk space issue and big tables
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A recurring and very common customer issue seen here at the Percona Support team involves how to make the ibdata1 file “shrink” within MySQL. I can only imagine there’s a degree of regret by some of the InnoDB architects on their design decisions regarding disk-space management by the shared tablespace* because this has been a big frustration for many MySQL users over the years.

There’s a very old bug (“InnoDB ibdata1 never shrinks after data is removed,” Sept. 8 2003) documenting user dissatisfaction. Shortly before that issue celebrated its 10th anniversary, James Day, MySQL senior principal support engineer at Oracle, posted a comment explaining

  [Read more...]
Measuring failover time for ScaleArc load balancer
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ScaleArc hired Percona to benchmark failover times for the ScaleArc database traffic management software in different scenarios. We tested failover times for various clustered setups, where ScaleArc itself was the load balancer for the cluster. These tests complement other performance tests on the ScaleArc software – sysbench testing for latency and testing for WordPress acceleration.

We tested failover times for Percona XtraDB Cluster (PXC) and MHA (any traditional MySQL replication-based solution works pretty much the same

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Benchmarking IBM eXFlash™ DIMM with sysbench fileio
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Diablo Technologies engaged Percona to benchmark IBM eXFlash™ DIMMs in various aspects. An eXFlash™ DIMM itself is quite an interesting piece of technology. In a nutshell, it’s flash storage, which you can put in the memory DIMM slots. Enabled by Diablo’s Memory Channel Storage™ technology, this practically means low latency and some unique performance characteristics.

These devices are special, because their full performance potential is unlocked by using multiple devices to leverage the parallelism of the memory subsystem. In a modern CPU there is more than one memory controller (4 is typical nowadays) and spreading eXFlash™ DIMMs across them will provide maximum performance. There are quite some details about the device that are omitted in this post, they can be found in

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Sysbench Benchmarking of Tesora’s Database Virtualization Engine
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Tesora, previously called Parelastic, asked Percona to do a sysbench benchmark evaluation of its Database Virtualization Engine on specific architectures on Amazon EC2.

The focus of Tesora is to provide a scalable Database As A Service platform for OpenStack. The Database Virtualization Engine (DVE) plays a part in this as it aims at allowing databases to scale transparently across multiple MySQL shards.

DVE was open sourced last

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Semi-sync replication is not slow!
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If you read Yoshinori's post about Semi-sync at Facebook, he lists the objective of using semi-sync as an alternative to running full durability on a master. That is to say that once you can guarantee writes have safely been shipped across the network, you may not strictly need to guarantee that they are safe locally.

This is something that I have been wanting to benchmark for a long time, and reading Jay's post about Semi-sync replication performance in MySQL 5.7 DMR4 and a conversation in last week's #dbhangops inspired me to explore this in more detail. For my tests, I will be using Master-Slave replication and three alternative definitions of

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Do not trust vmstat IOwait numbers
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I’ve been running a benchmark today on my old test box with conventional hard drives (no raid with BBU) and noticed something unusual in the CPU utilization statistics being reported.

The benchmark was run like this:

sysbench --num-threads=64 --max-requests=0 --max-time=600000 --report-interval=10 --test=oltp --db-driver=mysql --oltp-dist-type=special  --oltp-table-size=1000000   --mysql-user=root --mysql-password=password  run

Which means: create 64 threads and hammer the database with queries as quickly as possible. As the test was run on the localhost I would expect the benchmark to completely saturate the system – being either using CPU or being blocked on IO nature of this benchmark so it does not spend a lot on database locks, especially as this system has just 2 cores.

Looking at VMSTAT however I noticed

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How to improve InnoDB performance by 55% for write-bound loads
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During April’s Percona Live MySQL Conference and Expo 2014, I attended a talk on MySQL 5.7 performance an scalability given by Dimitri Kravtchuk, the Oracle MySQL benchmark specialist. He mentioned at some point that the InnoDB double write buffer was a real performance killer. For the ones that don’t know what the innodb double write buffer is, it is a disk buffer were pages are written before being written to the actual data file. Upon restart, pages in the double write buffer are rewritten to their data files if complete. This is to avoid data file corruption with half written pages. I knew it has an impact on performance, on ZFS since it is transactional I always disable it, but I never realized how important the performance

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Showing entries 1 to 10 of 222 10 Older Entries

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