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Displaying posts with tag: benchmark (reset)
MySQL Cluster 7.2: Over 8x Higher Performance than Cluster 7.1

Summary

The scalability enhancements delivered by extensions to multi-threaded data nodes enables MySQL Cluster 7.2 to deliver over 8x higher performance than the previous MySQL Cluster 7.1 release on a recent benchmark

What’s New in MySQL Cluster 7.2

MySQL Cluster 7.2 was released as GA (Generally Available) in February 2012, delivering many enhancements to performance on complex queries, new NoSQL Key / Value API, cross-data center replication and ease-of-use. These enhancements are summarized in the Figure below, and detailed in the MySQL Cluster New Features whitepaper

Figure 1: Next Generation Web Services, Cross Data Center Replication and Ease-of-Use

Once of the key enhancements delivered in MySQL …

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Performance Testing of MySQL Cluster: The flexAsynch Benchmark

Following the release of MySQL Cluster 7.2, the Engineering has been busy publishing a range of new performance benchmarks, most recently delivering 1.2 Billion UPDATE operations per Minute across a cluster of 30 x commodity Intel Xeon E5-based servers.

Figure 1: Linear Scaling of Write Operations

These performance tests have been run on the flexAsynch benchmark, so in the this blog, I wanted to provide a little more detail on that benchmark, and provide guidance on how you can use it in your own performance evaluations.

FlexAsynch is an open source, highly adaptable test suite that can be downloaded as part of the MySQL Cluster source tarball under the <storage/ndb/test/ndbapi> directory.

An …

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Benchmarking MySQL Replication with Multi-Threaded Slaves

The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6.

As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to:

· Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data)

· Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog)

The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application …

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MariaDB-5.5 Thread Pool Performance

MariaDB-5.5.21-beta is the first MariaDB release featuring the new thread pool. Oracle offers a commercial thread pool plugin for MySQL Enterprise, but now MariaDB brings a thread pool implementation to the community!

If you are not familiar with the term, please read the Knowledge Base article about it.

The main design goal of the thread pool is to increase the scalability of the MariaDB server with many concurrent connections. In order to test and demonstrate this, I have run the sysbench OLTP RO benchmark with up to 4096 threads to compare the new pool-of-threads and the traditional thread-per-connection scheduler:

Benchmark description:

  • sysbench multi table OLTP, readonly
  • 16 tables, totaling 40 mio …
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Optimizer tracing used by others!

In a previous post, I had explained how to use MySQL's optimizer tracing, a new feature which appeared in MySQL 5.6.3.

As a developer, it feels really good to see others adopt my work and make something useful out of it! My colleague Dimitri Kravtchuk, who is one of our top Benchmarking experts, has written a blog post where he shows how the optimizer tracing has helped him to figure out why, under load, once in a while and randomly, a query performed badly. His investigation technique may be reusable by other people, so I encourage you to read more about it, here.

How to log all MySQL queries in Drupal

In order to benchmark a Drupal site performance you need to see all the database queries related to your Drupal site. In case you don’t have access to the my.cnf file If you don’t have access to the my.cnf file, you can log the queries from the Drupal code itself: cp includes/database.mysql-common.inc includes/database.mysql-common.inc.backup.orig vim includes/database.mysql-common.inc […]

TPC-C like Benchmarks of Galera and Stock MySQL Replication

Vadim Tkachenko of Percona benchmarks Galera versus standalone Percona Server and stock MySQL replication using tpcc-mysql.

451 CAOS Links 2011.07.01

A herd of Hadoop announcements. Rockmelt raises $30m. And more.

A herd of Hadoop announcements
# Yahoo! and Benchmark Capital confirmed the formation of Hortonworks, an independent company focused on the development and support of Apache Hadoop.

# Cloudera announced the availability of Cloudera Enterprise 3.5 and the launch of Cloudera SCM Express, based on the new Service and Configuration Manager in Cloudera Enterprise 3.5.

# MapR …

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Aligning IO on a hard disk RAID – the Benchmarks

In the first part of this article I have showed how I align IO, now I want to share results of the benchmark that I have been running to see how much benefit can we get from a proper IO alignment on a 4-disk RAID1+0 with 64k stripe element. I haven’t been running any benchmarks in a while so be careful with my results and forgiving to my mistakes

The environment

Here is the summary of the system I have been running this on (for brevity I have removed some irrelevant information):

# Aspersa System Summary Report ##############################
    Platform | Linux
     Release | Ubuntu 10.04.2 LTS (lucid)
      Kernel | 2.6.32-31-server
Architecture | CPU = 64-bit, OS = 64-bit
# Processor …
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Innodb Compression: When More is Less

So Vadim posted on the MySQL Performance Blog about poor benchmarks when running innodb compressed pages.  I ran some tests a few weeks ago and did not see the same results as him and checked into my previous tests and compared them to his #’s.  In a round about way verifying his thoughts on Mutex contention I found that increasing the BP sized with compressed data decreases the transactional throughput. The test was run with an uncomressed data set size of 6GB, 3.1GB compressed read-only.

TPS
2G, NOZIP 3217.19
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