Or I could place in the title – “Yes, we done it!”

After reaching 500K QPS in Read-Only on SQL queries, it was natural to expect a much higher performance level from InnoDB Memcached Plugin which is by-passing all SQL related layers.. However the story is not simple, and yet far from finished

While for today we have already our first “preview” results showing that we’re able to reach over 1,000,000 Query/sec level with the latest MySQL 5.7 code:

click here to read the full article..

This is part two on a two-part series on the performance implications of in-flight data encryption with MySQL. In the first part, I focused specifically on the impact of using MySQL’s built-in SSL support with some rather surprising results. Certainly it was expected that query throughput would be lower with SSL than without, but I was rather surprised by the magnitude of the performance hit incurred at connection setup time. These results naturally lended themselves to some further investigation; in particular, I wanted to compare performance differences between MySQL’s built-in SSL encryption facilities and external encryption technologies, such as SSH tunneling. I’ll also be using this post to address a couple of questions posed in the comments on my original article. So, without further ado….

Test Environment

The …

NOTE: This is part 1 of what will be a two-part series on the performance implications of using in-flight data encryption.

Some of you may recall my security webinar from back in mid-August; one of the follow-up questions that I was asked was about the performance impact of enabling SSL connections. My answer was 25%, based on some 2011 data that I had seen over on yaSSL’s website, but I included the caveat that it is workload-dependent, because the most expensive part of using SSL is establishing the connection. Not long thereafter, I received a request to conduct some more specific benchmarks surrounding SSL usage in MySQL, and today I’m going to show the results.

First, the testing …

Yesterday we announced the GA release of Percona Server 5.6, the latest release of our enhanced, drop-in replacement for MySQL. Percona Server 5.6 is the best free MySQL alternative for demanding applications. Our third major release, Percona Server 5.6 offers all the improvements found in MySQL 5.6 Community Edition plus scalability, availability, backup, and security features some of which are found only in MySQL 5.6 Enterprise Edition.

Percona Server 5.6 comes with:

• General performance improvements
• Extensive diagnostics via TABLE/INDEX/USER …

With the close of call for papers earlier this month, the Percona Live London conference committee was in full swing this past week reviewing all of the many submissions for November’s Percona Live London MySQL Conference.

The submissions are far ranging and cover some really interesting topics, making the lineup for Percona Live London really strong! What the committee looks for in a submission is how much “value” a talk will bring to the conference – this is to say it needs to be far more that a product demo. As such, real-world experiences are receiving much more favorable reviews, along with talks that cover methodologies the attendees will …

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 …

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 …

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 …

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 …

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 …