Data inconsistencies in replication environments are a pretty common. There are lots of posts that explain how to fix those using pt-table-checksum and pt-table-sync. Usually we only care about the data but from time to time we receive this question in support:

How can I check the table definition consistency between servers?

Replication also allow us to have different table definition between master and slaves. For example, there are some cases that you need some indexes on slaves for querying purposes but are not really needed on the master. There are some other cases where those differences are just a mistake that needs to be fixed.

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On a recent engagement I worked with a customer who makes extensive use of UUID() values for their Primary Key and stores it as char(36), and their row count on this example table has grown to over 1 billion rows.

The table is INSERT-only (no UPDATEs or DELETEs), and the bulk of their retrieval are PK lookups. Lookups by PK were performing acceptably, but they were concerned with the space usage by the table as we were approaching 1TB (running with innodb_file_per_table=1 and Percona Server 5.5).

This schema model presents an increasing burden for backups since they use Percona XtraBackup, and so the question was asked: does their choice of an effectively random Primary Key based on UUID() impact their on-disk storage, and to what extent? And as a neat trick I show towards the end of this post how you can calculate the …

I ran into an interesting issue today, while examining some EXPLAIN outputs, and wanted to share the findings, as some of this is undocumented.

Basically, you can start with a very simple InnoDB table - 2 INT columns, Primary Key (PK) on the 1st column, regular index on the 2nd:

CREATE TABLE `t1` (
  `id1` int(10) unsigned NOT NULL,
  `id2` int(10) unsigned DEFAULT NULL,
  PRIMARY KEY (`id1`),
  KEY `id2` (`id2`)
) ENGINE=InnoDB;

The query is:

SELECT id1 FROM t1;

This is a straight-forward query with no WHERE clause.

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I ran into an interesting issue today, while examining some EXPLAIN outputs, and wanted to share the findings, as some of this is undocumented.

Basically, you can start with a very simple InnoDB table – 2 INT columns, Primary Key (PK) on the 1st column, regular index on the 2nd:

CREATE TABLE `t1` (
  `id1` int(10) unsigned NOT NULL,
  `id2` int(10) unsigned DEFAULT NULL,
  PRIMARY KEY (`id1`),
  KEY `id2` (`id2`)
) ENGINE=InnoDB;

The query is:

SELECT id1 FROM t1;

This is a straight-forward query with no WHERE clause.

Given no WHERE clause, we know there will be a full table or index scan. Let’s look at EXPLAIN:

mysql> EXPLAIN SELECT id1 FROM t1\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: t1
         type: index
possible_keys: NULL
          key: id2
      key_len: 5
          ref: NULL
         rows: 1 …

Each day there is probably work done to improve performance of the InnoDB storage engine and remove bottlenecks and scalability issues. Hence there was another one I wanted to highlight: Scalability issues due to tables without primary keys. This scalability issue is caused by the usage of tables without primary keys. This issue typically shows itself as contention on the InnoDB dict_sys mutex. Now the dict_sys mutex controls access to the data dictionary. This mutex is used at various important places throughout the InnoDB code and as such any contention on the dict_sys mutex is going to have a InnoDB system-wide negative affect.

The post InnoDB scalability issues due to tables without primary keys appeared first on ovais.tariq.

Each day there is probably work done to improve performance of the InnoDB storage engine and remove bottlenecks and scalability issues. Hence there was another one I wanted to highlight:

Scalability issues due to tables without primary keys

This scalability issue is caused by the usage of tables without primary keys. This issue typically shows itself as contention on the InnoDB dict_sys mutex. Now the dict_sys mutex controls access to the data dictionary. This mutex is used at various places. I will only mention a few of them:

• During operations such as opening and closing table handles, or
• When accessing I_S tables, or
• During undo of a freshly inserted row, or
• During other data dictionary modification operations such as CREATE TABLE, or
• Within the “Persistent Stats” subsystem, among other things.

Of course this list is not exhaustive but should …

I configure all our master databases to use row-based binary logging where I work. In my opinion it is a much safer option than statement-based replication. The advantages and disadvantages of both types of MySQL replication are detailed in the online documentation here. You can't view the events a slave is applying directly with 'show processlist' but by issuing 'show open tables where in use' you can detect what table is receiving the attention of the SQL thread. If you need more information the mysqlbinlog command must be used to decode the slaves relay logs or masters binary logs.

Our developers often change a lot of rows with a single update statement. This usually results in some reasonable replication lag on downstream slaves. Occasionally the lag continues to grow and eventually nagios …

From time to time I see articles in defense of natural primary keys against surrogate keys.I don't take an immovable stand on either side, as I have seen good cases for both. In general, I like the idea of a natural primary key, when I see one that it is really natural. Quite often, though, a natural primary key has proved itself faulty. And most of the times, when such faults happened, it was because of limited understanding of the data. I like to describe this kind of misinformation as data analysis culture clash.When choosing a natural primary key, one should consider which element, or group of elements, are unique in a given set. Not only that, they must be immutable, at least within that set.For example, in a group of people, we may assume that a combination of name, surname, date and place of birth is a good natural primary key. Well, no. It isn't, for several reasons. Read on for a few real cases.If we rule out the above combination, …

InnoDB uses an index-organized data storage technique, wherein the primary key acts as the clustered index and this clustered index holds the data. Its for this reason that understanding the basics of InnoDB primary key is very important, and hence the need for these notes.

Some people don't probably know, but there is a difference between how indexes work in MyISAM and how they work in InnoDB, particularly when talking from the point of view of performance enhancement. Now since, InnoDB is starting to be widely used, it is important we understand how indexing works in InnoDB. Hence, the reason for this post!