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Displaying posts with tag: mongodb (reset)
How to configure WEBM

Architecture of WEBM system.

Reference:

http://www.vmcd.org/2014/10/webm_v2-has-been-released/
http://www.vmcd.org/2014/09/webm-mysql-database-performance-web-monitor/

View this PDF:

http://www.vmcd.org/docs/How%20to%20configure%20WEBM.pdf

Log Buffer #430: A Carnival of the Vanities for DBAs

This Log Buffer Edition cuts through the crowd and picks some of the outstanding blog posts from Oracle, SQL Server and MySQL.


Oracle:

  • Continuous Delivery (CD) is a software engineering approach in which teams keep producing valuable software in short cycles and ensure that the software can be reliably released at any time.
  • Query existing HBase tables with SQL using Apache Phoenix.
  • Even though WebLogic with Active GridlLink are Oracle’s suggested approach to deploy Java applications that use Oracle Real Applications Clusters (RAC), …
[Read more]
Using Cgroups to Limit MySQL and MongoDB memory usage

Quite often, especially for benchmarks, I am trying to limit available memory for a database server (usually for MySQL, but recently for MongoDB also). This is usually needed to test database performance in scenarios with different memory limits. I have physical servers with the usually high amount of memory (128GB or more), but I am interested to see how a database server will perform, say if only 16GB of memory is available.

And while InnoDB usually respects the setting of innodb_buffer_pool_size in O_DIRECT mode (OS cache is not being used in this case), more engines (TokuDB for MySQL, MMAP, WiredTiger, RocksDB for MongoDB) usually get benefits from OS cache, and Linux kernel by default is generous enough to allocate as much memory as available. There I should note that while TokuDB (and TokuMX for MongoDB) supports DIRECT mode (that is bypass OS cache), we found there is a performance gain if OS cache is used for compressed pages.

[Read more]
Log Buffer #427: A Carnival of the Vanities for DBAs

This Log Buffer Edition covers various blog posts from the last week regarding Oracle, SQL Server and MySQL.

Oracle:

  • Merging Overlapping Date Ranges with MATCH_RECOGNIZE
  • The latest version of Enterprise Manager, EM 12.1.0.5, has been announced!
  • Kdump is the Linux kernel crash-dump mechanism. In the event of a server crash, Kdump creates a memory image (vmcore) that can help in determining the cause of the crash.
[Read more]
Percona Live Europe 2015! Call for speakers; registration open

Percona Live is moving from London to Amsterdam this year and the event is also expanding to three full days. Percona Live Europe 2015, September 21-23, will be at the Mövenpick Hotel Amsterdam City Centre. The call for speakers and Super Saver registration are now open. Hurry though because the deadline for submitting a speaking proposal is June 21st and Super Saver registration ends July 5th!

This year’s conference will feature one day of tutorials and two days of keynote talks and breakout …

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Auditing MySQL with McAfee and MongoDB

Greetings everyone! Let’s discuss a 3rd Party auditing solution to MySQL and how we can leverage MongoDB® to make sense out of all of that data.

The McAfee MySQL Audit plugin does a great job of capturing, at low level, activities within a MySQL server. It does this through some non-standard APIs which is why installing and configuring the plugin can be a bit difficult. The audit information is stored in JSON format, in a text file, by default.

There is 1 JSON object for each action that takes place within MySQL. If a user logs in, there’s an object. If that user queries a table, there’s an object. Imagine 1000 active connections from an application, each doing 2 queries per second. That’s 2000 JSON objects per second being written to the audit log. After 24 hours, that would be almost 173,000,000 audit entries!

How does one make sense of that many JSON objects? One option would be to write your own parser in …

[Read more]
MongoDB with Percona TokuMXse – experimental build RC5 is available!

While our engineering team is working on finalizing the TokuMXse storage engine, I want to provide an experimental build that you can try and test MongoDB 3.0 with our storage engine.

It is available here
percona.com/downloads/TESTING/Percona-TokuMXse-rc5/percona-tokumxse-3.0.3pre-rc5.tar.gz

To start MongoDB with TokuMXse storage engine use:

mongod --storageEngine=tokuft

I am looking for your feedback!

The post MongoDB with Percona TokuMXse – experimental build RC5 is available! appeared first on MySQL Performance Blog.

MongoDB’s flexible schema: How to fix write amplification

Being schemaless is one of the key features of MongoDB. On the bright side this allows developers to easily modify the schema of their collections without waiting for the database to be ready to accept a new schema. However schemaless is not free and one of the drawbacks is write amplification. Let’s focus on that topic.

Write amplification?

The link between schema and write amplification is not obvious at first sight. So let’s first look at a table in the relational world:

mysql> SELECT * FROM user LIMIT 2;
+----+-------+------------+-----------+-----------+----------------------------------+---------+-----------------------------------+------------+------------+
| id | login | first_name | last_name | city      | country                          | zipcode | address                           | password   | birth_year | …
[Read more]
Percona Acquires Tokutek : My Thoughts #3 : Fractal Tree Indexes

Last week I wrote up my thoughts about the Percona acquisition of Tokutek from the perspective of TokuDB and TokuMX[se]. In this third blog of the trilogy I'll cover the acquisition and the future of the Fractal Tree Index. The Fractal Tree Index is the foundational technology upon which all Tokutek products are built.



 So what is a Fractal Tree Index? To quote the Wikipedia page:
"a Fractal Tree index is a tree data structure that keeps data sorted and allows searches and …

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LinkBenchX: benchmark based on arrival request rate

An idea for a benchmark based on the “arrival request” rate that I wrote about in a post headlined “Introducing new type of benchmark” back in 2012 was implemented in Sysbench. However, Sysbench provides only a simple workload, so to be able to compare InnoDB with TokuDB, and later MongoDB with Percona TokuMX, I wanted to use more complicated scenarios. (Both TokuDB and TokuMX are part of Percona’s product line, in the case you missed Tokutek now part of the Percona family.)

Thanks to Facebook – they provide LinkBench, a benchmark that emulates the social graph …

[Read more]