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Displaying posts with tag: binary logs (reset)
MaxScale Binlog Server HOWTO: POC for Master Promotion without Touching any Slave

Note: DO NOT use this procedure in production, this is a proof of concept (POC).  MaxScale 1.1.0 does not yet fully support that procedure and things could go wrong in some situations (see at the end of the post for the details).

In my talk at PLMCE 2015, I presented an architecture to promote a slave as a new master without touching any other slave and I claimed that I tested it.  This HOWTO

MaxScale Binlog Server HOWTO: Operations (including Chaining)

In the Install and Configure HOWTO, we learned how to install and configure a MaxScale Binlog Server.  In this HOWTO, I will present the common operations that you might need to perform when using this software.  Those operations include:

Purging Binary Logs, Chaining Binlog Servers, Saving Binary Log Files in the Non-Default Directory, Downloading Binary Logs other than First, Listing Connected

Even Easier Master Promotion (and High Availability) for MySQL (no need to touch any slave)

Dealing with the failure of a MySQL master is not simple.  The most common solution is to promote a slave as the new master but in an environment where you have many slaves, the asynchronous implementation of replication gets in your way.  The problem is that each slave might be in a different state:

some could be very close to the dead master, some could be missing the latest transactions, and

MySQL Parallel Replication and Slave Group Commit

http://blog.booking.com/evaluating_mysql_parallel_replication_2-slave_group_commit.html

Follow the link above to read my latest article on the Booking.com developer blog.  It is about MySQL Parallel Replication and a very nice side effect of the MariaDB implementation: Slave Group Commit.

This is also a good opportunity to remind you that I will speak at Percona Live Santa Clara 2015 about 

Identifying useful info from MySQL row-based binary logs

As a MySQL DBA/consultant, it is part of my job to decode the MySQL binary logs – and there are a number of reasons for doing that. In this post, I’ll explain how you can get the important information about your write workload using MySQL row-based binary logs and a simple awk script.

First, it is important to understand that row-based binary logs contain the actual changes done by a query. For example, if I run a delete query against a table, the binary log will contain the rows that were deleted. MySQL provides the mysqlbinlog utility to decode the events stored in MySQL binary logs. You can read more about mysqlbinlog in detail in the reference manual here.

The following example illustrates how mysqlbinlog displays row events that specify data modifications. These correspond to events with the WRITE_ROWS_EVENT, UPDATE_ROWS_EVENT, …

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Binary log file size matters (sometimes)

I used to think one should never look at max_binlog_size, however last year I had a couple of interesting cases which showed that sometimes it may be very important variable to tune properly. I meant to write about it earlier but never really had a chance to do it. I have it now!

One of our customers was complaining that the database would lock up at random times and then it would go back to normal in just a few seconds. This was MySQL 5.0 running MyISAM/InnoDB mix, not heavily loaded. We used pt-stalk (at that time it was aspersa stalk) trying to figure out what is happening, however all we found was a spike in writes, many queries piled up and looking at the system process list it was quite obvious that page flush daemon was acting out. I/O Pattern was rather awkward – here is an output from …

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Setting up Master-Slave Replication with MySQL

Replication enables data from one MySQL server to be replicated on one or more other MySQL servers. Replication is mostly used as scale-out solution. In such a solution, all writes and updates take place on the master server, while reads take place on one or more slaves. This model is actually known as master-slave replication and this is the kind of replication that I will be setting up in this post.

Statement-based vs Row-based Replication

Replication as most people know it, has mostly been SQL statement propagation from master to slave. This is known as "statement-based" replication. But there is also another kind of replication that is available, "the row-based replication" and that has quite a lot of benefits. In this post I intend on highlighting the advantages and disadvantages of both the types of replication to help you choose the best one. I also follow up with my own recommendation.

Purging binary logs.

Being a MySQL DBA , one faces a common issue in replication environment -> Disk space issue on master, since the number of binary logs have increased. Now, one of the solution to this would be using expire_logs_days parameter in your mysql config file. But what if, the slave is lagging by few hours or if the slave is broken since few days and the binary logs are removed due to the parameter set. Whenever the salve comes up, it will go bonkers, knowing that the binary log where it last stopped no more exists.
I faced this issue a couple of times until I decided to automate it using a script. Herewith I am attaching the URL to my python script which can run regularly in cron. Features :

  • Checks the slaves connected to the master (I have limit it to 3 for now.)
  • Checks the last binary log file which is being used by the slave.
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Just how useful are binary logs for incremental backups?

We've written about replication slaves lagging behind masters before, but one of the other side effects of the binary log being serialized, is that it also limits the effectiveness of using it for incremental backup.  Let me make up some numbers for the purposes of this example:

  • We have 2 Servers in a Master-Slave topology.
  • The database size is 100 GB (same tables on each).
  • The slave machine barely keeps up with the master (at 90% capacity during peak, 75% during offpeak)
  • The peak window is 12 hours, the offpeak window is 12 hours.

Provided that the backup method was raw data files, it shouldn't take much more than 30 minutes to restore 100GB (50MB/s), but to replay one day of binary logs  it would take an additional 20 hours ((12 * …

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