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Displaying posts with tag: Benchmarks (reset)

MySQL and the SSB – Part 2 – MyISAM vs InnoDB low concurrency
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This blog post is part two in what is now a continuing series on the Star Schema Benchmark.

In my previous blog post I compared MySQL 5.5.30 to MySQL 5.6.10, both with default settings using only the InnoDB storage engine.  In my testing I discovered that innodb_old_blocks_time had an effect on performance of the benchmark.  There was some discussion in the comments and I promised to follow up with more SSB tests at a later date.

I also promised more low concurrency SSB tests when Peter blogged about the importance of performance at low concurrency.

The SSB
The SSB tests a

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Virident vCache vs. FlashCache: Part 2
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This is the second part in a two-part series comparing Virident’s vCache to FlashCache. The first part was focused on usability and feature comparison; in this post, we’ll look at some sysbench test results.

Disclosure: The research and testing conducted for this post were sponsored by Virident.

First, some background information. All tests were conducted on Percona’s Cisco UCS C250 test machine, and both the vCache and FlashCache tests used the same 2.2TB Virident FlashMAX II as the cache storage device. EXT4 is the filesystem, and CentOS 6.4 the operating system, although the pre-release modules I received from Virident required the use of the CentOS 6.2 kernel, 2.6.32-220, so that was the kernel in use for all of the benchmarks on

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Virident vCache vs. FlashCache: Part 1
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(This is part one of a two part series) Over the past few weeks I have been looking at a preview release of Virident’s vCache software, which is a kernel module and set of utilities designed to provide functionality similar to that of FlashCache. In particular, Virident engaged Percona to do a usability and feature-set comparison between vCache and FlashCache and also to conduct some benchmarks for the use case where the MySQL working set is significantly larger than the InnoDB buffer pool (thus leading to a lot of buffer pool disk reads) but still small enough to fit into the cache device. In this post and the next, I’ll present some of those

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MySQL and Percona Server in LinkBench benchmark
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Around month ago Facebook has announced the Linkbench benchmark that models the social graph OLTP workload. Sources, along with a very nice description of how to setup and run this benchmark, can be found here. We decided to run this benchmark for MySQL Server 5.5.30, 5.6.11 and Percona Server 5.5.30 and check how these servers will handle such OLTP workloads in the CPU and IO-bound cases. For this test we used a PowerEdge R720 box with a fast PCI-e flash card as storage.

By default linkbench dataset has 10M ids(after load of data size of datadir ~10GB). We used this dataset

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Benchmarking Percona Server TokuDB vs InnoDB
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After compiling Percona Server with TokuDB, of course I wanted to compare InnoDB performance vs TokuDB.
I have a particular workload I’m interested in testing – it is an insert-intensive workload (which is TokuDB’s strong suit) with some roll-up aggregation, which should produce updates in-place (I will use INSERT .. ON DUPLICATE KEY UPDATE statements for that), so it will produce all good amount of reads.

A few words about the hardware: I am going to use new the Dell PowerEdge R420 with two Intel(R) Xeon(R) CPU E5-2450 0 @ 2.10GHz, 48GB of RAM and SATA SSD: Kingston HyperX 3K 240 GB.

Workload: I will use two different schemas. The first schema is from sysbench, and


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More on MySQL transaction descriptors optimization
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Since my first post on MySQL transaction descriptors optimization introduced in Percona Server 5.5.30-30.2 and a followup by Dimitri Kravchuk, we have received a large number of questions on why the benchmark results in both posts look rather different. We were curious as well, so we tried to answer that question by retrying benchmarks on various combinations of hardware and dataset sizes, including the ones that are as close as possible to Dimitri’s environment. To put a long story short, the results

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Testing the Micron P320h
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The Micron P320h SSD is an SLC-based PCIe solid-state storage device which claims to provide the highest read throughput of any server-grade SSD, and at Micron’s request, I recently took some time to put the card through its paces, and the numbers are indeed quite impressive.

For reference, the benchmarks for this device were performed primarily on a Dell R720 with 192GB of RAM and two Xeon E5-2660 processors that yield a total of 32 virtual cores. This is the same machine which was used in my previous benchmark run. A small handful of additional tests were also performed using the Cisco UCS C250. The operating system in use was CentOS 6.3, and for the sysbench fileIO tests, the EXT4 filesystem was used. The card itself is the 700GB model.

So let’s take

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Memory allocators: MySQL performance improvements in Percona Server 5.5.30-30.2
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In addition to the problem with trx_list scan we discussed in Friday’s post, there is another issue in InnoDB transaction processing that notably affects MySQL performance – for every transaction InnoDB creates a read view and allocates memory for this structure from heap. The problem is that the heap for that allocation is destroyed on each commit and thus the read view memory is reallocated on the next transaction.

There

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trx descriptors: MySQL performance improvements in Percona Server 5.5.30-30.2
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One major problem in terms of MySQL performance that still stands in the way of InnoDB scalability is the trx_list scan on consistent read view creation. It was originally reported as a part of MySQL bug #49169 and can be described as follows. Whenever a connection wants to create a consistent read, it has to make a snapshot of the transaction states to determine which transactions are seen in the view later. To this end, InnoDB scans trx_list (i.e. the list of currently open transactions) and copies IDs of transactions that have not yet been committed at the

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Why MySQL Performance at Low Concurrency is Important
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A few weeks ago I wrote about “MySQL Performance at High Concurrency” and why it is important, which was followed up by Vadim’s post on ThreadPool in Percona Server providing some great illustration on the topic. This time I want to target an opposite question: why MySQL performance at low concurrency is important for you.

I decided to write about this topic as a number of recent blog

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10 Newer Entries Showing entries 31 to 40 of 222 10 Older Entries

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