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Displaying posts with tag: Benchmarks (reset)
TokuDB vs InnoDB in timeseries INSERT benchmark

This post is a continuation of my research of TokuDB’s  storage engine to understand if it is suitable for timeseries workloads.

While inserting LOAD DATA INFILE into an empty table shows great results for TokuDB, what’s more interesting is seeing some realistic workloads.

So this time let’s take a look at the INSERT benchmark.

What I am going to do is to insert data in 16 parallel threads into the table from the previous post:

CREATE TABLE `sensordata` (
  `ts` int(10) unsigned NOT NULL DEFAULT '0',
  `sensor_id` int(10) unsigned NOT NULL,
  `data1` double NOT NULL,
  `data2` double NOT NULL,
  `data3` double NOT NULL,
  `data4` double NOT NULL,
  `data5` double NOT …
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Considering TokuDB as an engine for timeseries data

I am working on a customer’s system where the requirement is to store a lot of timeseries data from different sensors.

For performance reasons we are going to use SSD, and therefore there is a list of requirements for the architecture:

  • Provide high insertion rate
  • Provide a good compression rate to store more data on expensive SSDs
  • Engine should be SSD friendly (less writes per timeperiod to help with SSD wear)
  • Provide a reasonable response time (within ~50 ms) on SELECT queries on hot recently inserted data

Looking on these requirements I actually think that TokuDB might be a good fit for this task.

There are several aspects to consider. This time I want to compare TokuDB vs InnoDB on an initial load time and space consumption.

Let’s …

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InnoDB Full-text Search in MySQL 5.6: Part 3, Performance

This is part 3 of a 3 part series covering the new InnoDB full-text search features in MySQL 5.6. To catch up on the previous parts, see part 1 or part 2

Some of you may recall a few months ago that I promised a third part in my InnoDB full-text search (FTS) series, in which I’d actually take a look at the performance of InnoDB FTS in MySQL 5.6 versus traditional MyISAM FTS. I hadn’t planned on quite such a gap between part 2 and part 3, but as they say, better late than never. Recall that we have been working with two data sets, one which I call SEO (8000-keyword-stuffed web pages) and the other which I call DIR (800K directory records), and we are comparing MyISAM FTS in …

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When it’s faster to use SQL in MySQL NDB Cluster over memcache API

Memcache access for MySQL Cluster (or NDBCluster) provides faster access to the data because it avoids the SQL parsing overhead for simple lookups – which is a great feature. But what happens if I try to get multiple records via memcache API (multi-GET) and via SQL (SELECT with IN())? I’ve encountered this a few times now, so I decided to blog about it. I did a very simple benchmark with the following script:

#!/bin/bash
mysql_server="192.168.56.75"
mc_server="192.168.56.75"
mysql_cmd="mysql -h${mysql_server} --silent --silent"
mysql_schema="percona"
mysql_table="memcache_t"
mc_port=11211
mc_prefix="mt:"
function populate_data () {
  nrec=$1
  $mysql_cmd -e "delete from ${mysql_table};" $mysql_schema > /dev/null 2>&1
  for rec in `seq 1 $nrec`
  do
    $mysql_cmd -e "insert into ${mysql_table} values ($rec, repeat('a',10), 0, 0);" $mysql_schema > /dev/null 2>&1
  done
}
function mget_via_sql() {
  nrec=$1
  in_list=''
  for rec in …
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Shard-Query 2.0 performance on the SSB with InnoDB on Tokutek’s MariaDB distribution

Scaling up a workload to many cores on a single host

Here are results for Shard-Query 2.0 Beta 1* on the Star Schema Benchmark at scale factor 10.  In the comparison below the “single threaded” response times for InnoDB are the response times reported in my previous test which did not use Shard-Query.

Shard-Query configuration

Shard-Query has been configured to use a single host.  The Shard-Query configuration repository is stored on the host.  Gearman is also running on the host, as are the Gearman workers.  In short, only one host is involved in the testing.

The …

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TokuDB vs Percona XtraDB using Tokutek’s MariaDB distribution

Following are benchmark results comparing Tokutek TokuDB and Percona XtraDB at scale factor 10 on the Star Schema benchmark. I’m posting this on the Shard-Query blog because I am going to compare the performance of Shard-Query on the benchmark on these two engines. First, however, I think it is important to see how they perform in isolation without concurrency.

Because I am going to be testing Shard-Query, I have chosen to partition the “fact” table (lineorder) by month. I’ve attached the full DDL at the end of the post as well as the queries again for reference.

I want to note a few things about the results:
First and foremost, TokuDB was configured to use quicklz compression (the default) and InnoDB compression was not used. No tuning of TokuDB was performed, which means it will use up to 50% of memory by default. Various InnoDB tuning options were set (see the end of the post) but the most important is that the …

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MySQL and the SSB – Part 2 – MyISAM vs InnoDB low concurrency

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 database’s ability to optimize queries for a star schema. A star …

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Virident vCache vs. FlashCache: Part 2

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 both systems. The benchmark tool used was sysbench 0.5 and the version of MySQL used was …

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Virident vCache vs. FlashCache: Part 1

(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 results.

Disclosure: The research and testing for this post series was sponsored by Virident.

Usability is, to some extent, a subjective call, as I may have preferences …

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MySQL and Percona Server in LinkBench benchmark

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 to check server behavior when data fully fits …

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