Today’s episode is all about Valgrind – from the pro’s to the con’s, from the why to the how! This episode will be of interest to anyone who is or wants to work with Valgrind on a regular or semi-regular basis.

1. Pro’s/Why
2. Con’s
3. How
   1. Using the latest version
      sudo [yum/apt-get] install valgrind
      #OR#
      sudo [yum/apt-get] remove valgrind
      sudo [yum/apt-get] install bzip2 glibc*
      wget http://valgrind.org/downloads/valgrind-3.10.1.tar.bz2
      tar -xf valgrind-3.10.1.tar.bz2; cd valgrind-3.10.1
      ./configure; make; sudo make install
      valgrind –version # This should now read 3.10.1
   2. VGDB (cd ./mysql-test)
      ./lib/v1/mysql-test-run.pl –start-and-exit –valgrind –valgrind-option=”–leak-check=yes”
      –valgrind-option=”–vgdb=yes” …

Execute “Show Engine InnoDB Status;” query analyze the result in “Transaction” section, find out problematic queries.

Now next step is to how to avoid this problem, and here is a solution:

Deadlocks are a classic problem in transactional databases, but they are not dangerous unless they are so frequent that you cannot run certain transactions at all. Normally, you must write your applications so that they are always prepared to re-issue a transaction if it gets rolled back because of a deadlock.

• Always be prepared to re-issue a transaction if it fails due to deadlock. Deadlocks are not dangerous. Just try again.
• Keep transactions small and short in duration to make them less prone to collision.

Reference :  …

It mentions in the message that you can try to repair it. Also, if you look at the actual FILEPATH you get, you can find out more:

• if it is something like /tmp/#sql_actor_return it means that MySQL needs to create a temporary table because of the query size. It stores it in /tmp, and that there is not enough space in your /tmp for that temporary table. increase the tmp_table_size variable and /tmp/ partition size
• If it contains the name of an actual table instead, it means that this table is very likely corrupted and you should repair it using REPAIR TABLE

If a table-full error occurs, it may be that the disk is full or that the table has reached its maximum size. The effective maximum table size for MySQL databases is usually determined by operating system constraints on file sizes, not by MySQL internal limits.

Limits on Table size : The following table lists some examples of operating system file-size limits. This is only a rough guide and is not intended to be definitive.

If you do encounter a full-table error, there are several reasons why it might have occurred:

• The disk might be full.
• The InnoDB storage engine maintains InnoDB tables within a tablespace that can be created from several files. This enables a table to exceed the maximum individual file size , check InnoDB tablespace (ibdata1)
• You are using MyISAM tables on an operating …

One day on production server I encountered this error message, So I found out a solution for it as:

There are multiple reasons, listed below:

1. You’ve run out of memory available to MySQL.This is the most likely problem you’re facing. Each connection in MySQL’s connection pool requires memory to function, and if this resource is exhausted, no further connections can be made. Of course, the memory footprints and maximum packet sizes of various operations can be tuned in your equivalent to my.cnf if you discover this to be an issue.

You can calculate MySQL memory using this tool – http://www.mysqlcalculator.com/

This shows maximum size a MySQL should use in your environment, in my case it’s a dedicated MYSQL …

This is your very first post. Click the Edit link to modify or delete it, or start a new post. If you like, use this post to tell readers why you started this blog and what you plan to do with it.

Happy blogging!

When a new version of MySQL appears, the first source of information for the brave experimenter is a page in the manual named What is new in MySQL X.X, also known as MySQL in a nutshell. For MySQL 5.7, the in-a-nutshell page lists quite a lot of changes. In that page, the list of removed features is enough to send a chill down the spine of most any DBA. Some of the items in the deprecation section are removals in disguise, as they require immediate, rather than delayed, action to use the new version with existing application (SET …

ScaleDB extends MySQL for high-velocity high-volume data, enabling near real-time analytics across massive streams of data. Like Hadoop, ScaleDB leverages a cluster of commodity machines with low-cost spinning disks for storage, mitigating the typical trade-offs between data fidelity and the volume of data and time analyzed. NoSQL and Hadoop are excellent choices for unstructured data, or data variety challenges. However, if your data is structured time-series data, and generated at high-velocity and high-volume, ScaleDB is the tool for you. On a nine-node cluster, ScaleDB inserts millions of rows per second and queries up to 1000 times faster, more than enough speed for today’s most demanding applications.

ResponsibilitiesLooking for C/C++ experience, ideally with experience with database server internals. You will design and implement a next generation database storage engine. You will have ownership for one or more modules of the …

#DBHangOps 08/06/15 -- Orchestrator and Binlog Servers and more!

Hello everybody!

Join in #DBHangOps this Thursday, August, 06, 2015 at 11:00am pacific (18:00 GMT), to participate in the discussion about:

• Orchestrator and Binlog Servers from Shlomi Noach
• Configuration vs. Orchestration

You can check out the event page at https://plus.google.com/events/ci32euumljnmivfo8kkh9j8kum8 on Thursday to participate.

As always, you can still watch the #DBHangOps twitter search, the @DBHangOps twitter feed, or this blog post to get a link for the google hangout on Thursday!

See all of you on Thursday!

You can catch a …

Baron Schwartz will be speaking on Building Microservices with Go at OSCON EU on October 26th.

Below is an overview;

Go is great for building HTTP and RPC services. VividCortex’s infrastructure is Go-based, and there are a lot of lessons to learn from the experience building it. Here are some of the things we needed to do above and beyond what the standard libraries provide:

• Using net/http effectively
• Building an actually sane REST framework in Go
• Dealing with garbage collection
• Building a build system
• Continuous integration and deployment
• Running services (daemons)
• Runtime inspection of all in-flight requests
• Interacting with databases, caches, and queues
• Building staging and development environments