Categories
All Database Operations Scalability Web Operations

5 Ways to Boost MySQL Scalability

There are a lot of scalability challenges we see with clients over and over. The list could easily include 20, 50 or even 100 items, but we shortened it down to the biggest five issues we see.

1. Tune those queries

By far the biggest bang for your buck is query optimization. Queries can be functionally correct and meet business requirements without being stress tested for high traffic and high load. This is why we often see clients with growing pains, and scalability challenges as their site becomes more popular. This also makes sense. It wouldn’t necessarily be a good use of time to tune a query for some page off in a remote corner of your site, that didn’t receive real-world traffic. So some amount of reactive tuning is common and appropriate.

Enable the slow query log and watch it. Use mk-query-digest, the great tool from Maatkit to analyze the log. Also make sure the log_queries_not_using_indexes flag is set.  Once you’ve found a heavy resource intensive query, optimize it!  Use the EXPLAIN facility, use a profiler, look at index usage and create missing indexes, and understand how it is joining and/or sorting.

Also: Why generalists are better at scaling the web

2. Employ Master-Master Replication

Master-master active-passive replication, otherwise known as circular replication, can be a boon for high availability, but also for scalability.  That’s because you immediately have a read-only slave for your application to hit as well.  Many web applications exhibit an 80/20 split, where 80% of activity is read or SELECT and the remainder is INSERT and UPDATE.  Configure your application to send read traffic to the slave or rearchitect so this is possible.  This type of horizontal scalability can then be extended further, adding additional read-only slaves to the infrastructure as necessary.

If you’re setting up replication for the first time, we recommend you do it using hotbackups. Here’s how.

Keep in mind MySQL’s replication has a tendency to drift, often silently from the master. Data can really get out of sync without throwing errors! Be sure to bulletproof your setup with checksums.

Related: Why you can’t find a MySQL DBA

3. Use Your Memory

It sounds very basic and straightforward, yet there are often details overlooked.  At minimum be sure to set these:

  • innodb_buffer_pool_size
  • key_buffer_size (MyISAM index caching)
  • query_cache_size – though beware of issues on large SMP boxes
  • thread_cache & table_cache
  • innodb_log_file_size & innodb_log_buffer_size
  • sort_buffer_size, join_buffer_size, read_buffer_size, read_rnd_buffer_size
  • tmp_table_size & max_heap_table_size

Read: Why Twitter made a shocking admission about their data centers in the IPO

4. RAID Your Disk I/O

What is underneath your database?  You don’t know?  Well please find out!  Are you using RAID 5?  This is a big performance hit.  RAID5 is slow for inserts and updates.  It is also almost non-functional during a rebuild if you lose a disk.  Very very slow performance.  What should I use instead?  RAID 10 mirroring and striping, with as many disks as you can fit in your server or raid cabinet.  A database does a lot of disk I/O even if you have enough memory to hold the entire database.  Why?  Sorting requires rearranging rows, as does group by, joins, and so forth.  Plus the transaction log is disk I/O as well!

Are you running on EC2?  In that case EBS is already fault tolerant and redundant.  So give your performance a boost by striping-only across a number of EBS volumes using the Linux md software raid.

Also checkout our Intro to EC2 Cloud Deployments.

Also of interest autoscaling MySQL on EC2.

Also: Why startups are trying to do without techops and failing

5. Tune Key Parameters

These additional parameters can also help a lot with performance.

innodb_flush_log_at_trx_commit=2

This speeds up inserts & updates dramatically by being a little bit lazy about flushing the innodb log buffer.  You can do more research yourself but for most environments this setting is recommended.

innodb_file_per_table

Innodb was developed like Oracle with the tablespace model for storage.  Apparently the kernel developers didn’t do a very good job.  That’s because the default setting to use a single tablespace turns out to be a performance bottleneck.  Contention for file descriptors and so forth.  This setting makes innodb create tablespace and underlying datafile for each table, just like MyISAM does.

Read this: Why a four letter word still divides dev and ops

Made it to the end eh?!?! Grab our newsletter.

Categories
All Cloud Computing Database Operations Web Operations Website Basics

IOPs – What is it and why is it important?

IOPs are an attempt to standardize comparison of disk speeds across different environments.  When you turn on a computer, everything must be read from disk, but thereafter things are kept in memory.  However applications typically read and write to disk frequently.  When you move to enterprise class applications, especially relational databases, a lot of disk I/O is happening so performance of disk resources is crucial.

For a basic single SATA drive that you might have in server or laptop, you can typically get 30-40 IOPs from it.  These numbers vary if you are talking about random versus sequential reads or writes.  Picture the needle on a vinyl record.  It moves quicker around the center, and slower around the outside.  That’s what’s happening the the magnetic needle inside your harddrive too.

In Amazon EC2 environment, there is a lot of variability in performance from EBS.  You can stripe across four separate EBS volumes which will be on four different locations on the underlying RAID array and you’ll get a big boost in disk I/O.  Also disk performance will vary from an m1.small, m1.large and m1.xlarge instance type, with the latter getting the lions share of network bandwidth, so better disk I/O performance.  But in the end your best EBS performance will be in the range of 500-1000 IOPs.  That’s not huge by physical hardware standards, so an extremely disk intensive application will probably not perform well in the Amazon cloud.

Still the economic pressures and infrastructure and business flexibility continue to push cloud computing adoption, so expect the trend to continue.

Quora discussion – What are IOPs and why are they important?

Categories
All Database Operations Web Operations Website Basics

Extract Transform & Load – What is it and why is it important?

So-called ETL relates to moving data from external sources into and out of relational databases or data warehouses.

Extract

Source systems may store data in an infinite variety of formats.  Extracting involves getting that data into common files for moving to the destination system.  CSV file also known as comma separated values is named because each of the records is stored as one line in the file, and fields are separated by commas, and often surrounded by quotes as well.  In MySQL INTO OUTFILE syntax can perform this function.  If you have a lot of tables to work with, you can script the process using the data dictionary as a lookup for table names, and create a .mysql script to then run with the mysql shell.  In Oracle you would use the spool command in SQL*Plus the command line shell.  Spool sends subsequent output from the screen also to a file.

Transform

This step involves modifying the extracted data in preparation for moving it into the target database server.  It may involve sweeping out blank records, or rearranging columns, or breaking files into smaller subsets of data.  You might also map values differently for instance if one column in the source database was gender with values M/F you might transform those to the strings “Male” and “Female” if that is more useful for your target database server.  Or you might transform those to numerical values, for instance Male & Female might be 0/1 in your target database.

Although I myriad of high level GUI tools exist to perform these functions, the Unix operating system includes a plethora of very powerful tools that every experience System Administrator is familiar with.  Those include grep & sed which operate on regular expressions and can perform data transformation at lightening speed.  Then there is sort which can sort data and send the results to stdout or the file of your choosing.  Other tools include wc – word count, cut which can remove columns and so forth.
Load

This final step involves moving the data into the database server, and it’s final target tables.  For instance in MySQL this might be done with the LOAD DATA INFILE syntax, while in Oracle you might use SQL*Loader, which is a very fast flat file dataloader.

Quora discussion by Sean Hull – What is ETL?