MySQL table locks solution -> InnoDb / Partitions

You should think about partitioning the table for a big reason.

All indexes you have on a giant table, even just one index, can generated a lot of CPU load and disk I/O just to perform index maintenance when executing INSERTs, UPDATEs, and DELETEs.

I wrote an earlier post back on October 7, 2011 on why Table Partitioning would be a big help. Here is one excerpt from my past post:

Partitioning of data should serve to group data that are logically and cohesively in the same class. Performance of searching each partition need not be the main consideration as long as the data is correctly grouped. Once you have achieved the logical partitioning, then concentrate on search time. If you are just separating data by id only, it is possible that many rows of data may never be accessed for reads or writes. Now, that should be a major consideration: Locate all ids most frequently accessed and partition by that. All less frequently accessed ids should reside in one big archive table that is still accessible by index lookup for that 'once in a blue moon' query.

You can read my entire post later on this.

To cut right to the chase, you need to research and find out what data is rarely used in your 10GB table. That data should be placed in an archive table that is readily accessible should you need adhoc queries for a historical nature. Migrating that archival from the 10GB, followed by OPTIMIZE TABLE on the 10GB table, can result in a Working Set that is faster to run SELECTs, INSERTs, UPDATEs, and DELETEs. Even DDL would go faster on a 2GB Working Set than a 10GB table.

UPDATE 2012-02-24 16:19 EDT

Two points to consider

1. From your comment, it sounds like normalization is what you may need.
2. You may need to migrate out everything over 90 days old into an archive table but still access archive and working set at the same time. If your data is all MyISAM, I recommend using the MERGE storage engine. First, you create the MERGE table map once that unites a working set MyISAM table and an archive MyISAM table. You would keep data less than 91 days in one MyISAM table and rollover any data over 90 days old into the archive. You would query the MERGE table map only.

Here are two posts I made on how to use it:

• get column from too many tables in mysql
• Separate tables or partition one huge table?

Here is an additional post I made on tables with a lot of columns

Too many columns in MySQL

key_buffer_size ? RAM size?

On huge tables, indexes, especially if they are not "appended to", cause disk hits -- whether MyISAM or InnoDB.

var0, being an AUTO_INCREMENT, will be "appended to" the end. Essentially no disk hits for it. I can't tell about the other 4 indexes. Let's say they are all very random. This implies that each row inserted will need 4 disk hits. On normal drives that means about 25 rows inserted per second.

Solutions...

RAID striping (0,5,6,10). That will give you a factor of improvement.

SSDs. $$$

PARTITIONing. This may help. It may also help with some SELECTs. To discuss further, please reveal some of the semantics of the indexed fields. (dates? md5s? names?) Also provide some of the SELECTs, so we can optimize them at the same time. The "partition key" must be part of any UNIQUE key. This is not a problem with the AUTO_INCREMENT, but it may be with the other UNIQUE key.

Nothing (yet) says whether the Engine will make any difference.