Mysql – InnoDB vs MyISAM with many indexes

indexinnodbmyisamMySQL

I am not sure if there is a right or wrong answer to this question, as I suppose it severely depends on the situation, but for the sake of a mental exercise, I'll go ahead and ask it anyway:

I have a MyISAM table in my database that stands central to my site. There are many reference tables created around it and many other tables that link directly to row ids from this table. The table is about 260k rows in size, with 28 fields which for the most part is varchars and ints. I have about 15 indexes on it (the data is about 70 MiB, indexes are about 80 MiB). There are maybe several hundred writes a day, versus the tens of thousands of reads. My databases are located on an SSD drive.

Now my question is; would be be beneficial to alter this table to a InnoDB table? I am working on extending my systems to include API traffic as well, meaning that the table will even the queried even more and I want to make sure that everything runs as smooth as possible. Because of this, I'm slightly leaning towards converting it to InnoDB. However, since the table requires many indexes, I'm thinking MyISAM might work more effectively. Can anyone help me make up my mind? Thanks in advance1

Edit: (added by jcolebrand from a comment)

I have added the indexes a long time ago and I changed some things to the PHP code base, so maybe some indexes are out-dated, but overall; yes, they are all used. I run many different types of queries on the table. Different query, different index. But my main question here does not concern the table read performance, but how it performs with many indexes. InnoDB indexes are 'leaved'/ stored with the data, instead of MyISAM's key-file principle. I am just worried that this might cause enough of a performance drop not to outweigh the table lock issue.

Best Answer

There are maybe several hundred writes a day, versus the tens of thousands of reads. My databases are located on an SSD drive.

Based on this statement, let's play with some numbers. Lets's say there are 500 writes a day and 20,000 reads a day. That computes out to the following

97.56% reads per day
2.44% writes per day
40 reads / write

As much as I love InnoDB, I would have to choose MyISAM in this case for several reasons

REASON #1

You only have 150MiB of MyISAM tables (70MiB Data, 80 MiB Indexes)

REASON #2

InnoDB indexes tend to get very bloaty because Secondary Indexes have keys into the Clustered Index. This always results in a double index lookup. This can be overlooked with large, write-heavy datasets.

REASON #3

InnoDB tablespaces tend to get very bloaty because of MVCC being created and discarded without an automatic reclaiming of disk space:

With innodb_file_per_table disabled, the system tablespace file ibdata1 would steadily grow with 0% chance of reclaiming of disk space. You would have to convert InnoDB storage engine to use innodb_file_per_table.
With innodb_file_per_table enabled, you could go to the individual InnoDB and run of the the following to physically shrink the InnoDB table mydb.mytable:
- OPTIMIZE TABLE mydb.mytable;
- ALTER TABLE mydb.mytable ENGINE=InnoDB;

All this can be avoid with MyISAM

REASON #4

InnoDB protects individual rows by performing MVCC for transaction control. The overhead generated for reads in a day would probably be greater than 150 MiB.

I can probably name 2 or 3 more reasons, but let's cut to the chase: Is there anything that can improve performance for MyISAM in your case? Why, yes there is.

Your said the following

The table is about 260k rows in size, with 28 fields which for the most part is varchars and ints

If you have many varchars, there is something you can do to increase read/write performance. For any MyISAM table mydb.mytable: run this command:

ALTER TABLE mydb.mytable ROW_FORMAT=Fixed;

What will this do, this will treat all VARCHARs as CHARs. Every row will be the exact same length. This will increase disk space 80%-100%. In your case, let's assume it doubles your 150 MiB MyISAM table to 300 MiB. Where is the benefit? Your MyISAM table can now be read/written anywhere from 20% - 30% faster without changing anything else I learned that from pages 72,73 from MySQL Database Design and Tuning.

I have written about this in the past:

Which is faster, InnoDB or MyISAM? (May 03, 2012)
Which mysql storage engine to choose? (May 02, 2012)
Best of MyISAM and InnoDB (Sep 20, 2011)
Which DBMS is good for super-fast reads and a simple data structure? (Aug 12, 2011)
What is the performance impact of using CHAR vs VARCHAR on a fixed-size field? (May 10, 2011)

Related Solutions

MySQL: reducing ibdata file size for MyISAM tables

I already answered this in StackOverflow : https://stackoverflow.com/a/11636341/491757

If you want to defrag all your MyISAM tables, here is a shell script to do so...

MYSQL_USER=root
MYSQL_PASS=rootpassword
MYSQL_CONN="-u${MYSQL_USER} -p${MYSQL_PASS}"
SQL="SELECT CONCAT('OPTIMIZE TABLE ',table_schema,'.',table_name,';') "
SQL="${SQL} FROM information_schema.tables "
SQL="${SQL} WHERE engine='MyISAM' AND table_schema NOT IN "
SQL="${SQL} ('information_schema','performance_schema','mysql')"
mysql ${MYSQL_CONN} -ANe"${SQL}" > GlobalMyISAMOptmizeTable.sql
less GlobalMyISAMOptmizeTable.sql

Once you trust the script visually, just run it

mysql ${MYSQL_CONN} < GlobalMyISAMOptmizeTable.sql

Give it a Try !!!

Mysql – Simple queries taking ages to run after changing from MyISAM to InnoDB

A few notes and suggestions:

I was asking for the innodb% params to verify you're not running with silly defaults. You're not, and setup looks OK.

The inbound_link_changes table doesn't have a PRIMARY KEY. It should, as with all InnoDB tables, since these use a clustered index, which is the PRIMARY KEY. Yours does not have one, so it's clustered by internal row id, which is not optimal. Is there any UNIQUE combination on this table?

If not, I recommend making up a surrogate key, via AUTO_INCREMENT.

This could actually affect your query, since secondary keys are affected by clustering index (explanation is outside scope of this answer).

In addition, consider setting up an index on (link_id, change_type). Since you're giving away change_type as constant, this will be taken into account when looking up the index.