This week is special and full of anniversaries for me. This week 5 years ago I left Oracle behind and joined Percona... Same week 5 years ago I had written something about MySQL in this blog for the first time in my life. 5 years ago I've created my Facebook account that I actively (ab)use for discussing work-related issues. So, to summarize, it's a five years anniversary of my coming out as a MySQL Entomologist, somebody who writes and speaks about MySQL and bugs in MySQL in public! These 5 years were mostly awesome.

I decided to celebrate with yet another post in this relatively new series and summarize in short what interesting things I studied, …

In part 1 and part 2 of this blog series, I showed how a DBA could configure MySQL or MariaDB to automatically drop old partitions. Some readers mentioned that they would also like for new partitions to be automatically created. In this blog post, I will show a stored procedure that can automatically create new partitions, and I will tie ... Read More

In a previous blog post, I showed how a DBA could configure MySQL or MariaDB to automatically drop old partitions. Some readers provided some feedback on some issues that they’ve run into while doing similar operations. Specifically: It can sometimes help to maintain an empty first partition when partitioning by dates, since partition pruning cannot always eliminate the first partition. ... Read More

A MariaDB Support customer recently asked how they could automatically drop old partitions after 6 months. MariaDB and MySQL do not have a mechanism to do this automatically out-of-the-box, but it is not too difficult to create a custom stored procedure and an event to call the procedure on the desired schedule. In this blog post, I will show one ... Read More

In this blog, we’ll quickly look at MySQL partitioning.

Partitioning is a way in which a database (MySQL in this case) splits its actual data down into separate tables, but still get treated as a single table by the SQL layer.

When partitioning, it’s a good idea to find a natural partition key. You want to ensure that table lookups go to the correct partition or group of partitions. This means that all SELECT, UPDATE, DELETE should include that column in the WHERE clause. Otherwise, the storage engine does a scatter-gather, and queries ALL partitions in a UNION that is not concurrent.

Generally, you must add the partition key into the primary key along with the auto increment, i.e., PRIMARY KEY (part_id,id). If you …

Sometimes MySQL surprises you in ways you would have never imagined.

Would you think that the order in which the indexes appear in a table matters?
It does. Mind you, not the order of the columns - the order of the indexes.
MySQL optimizer can, in specific circumstances, take different paths, sometimes with nefarious effects.


Please consider the following table:

CREATE TABLE `mypartitionedtable ` (
  `HASH_ID` char(64) NOT NULL,
  `RAW_DATA` mediumblob NOT NULL,
  `EXPIRE_DATE` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
  KEY `EXPIRE_DATE_IX` (`EXPIRE_DATE`),
  KEY `HASH_ID_IX` (`HASH_ID`)
) ENGINE=TokuDB DEFAULT CHARSET=latin1 ROW_FORMAT=TOKUDB_UNCOMPRESSED
/*!50100 PARTITION BY RANGE (UNIX_TIMESTAMP(EXPIRE_DATE))
(PARTITION p2005 VALUES LESS THAN (1487847600) ENGINE = …

MySQL Cluster does an automatic sharding/partitioning to the tables across data nodes, enabling databases to scale horizontally to serve read and write-intensive workloads, but what is the default sharding key used in partitioning the data?
According to the recent update (Oct, 2016) of the MySQL Cluster white paper, primary key is the default sharding key:

By default, sharding is based on hashing of the primary key, which generally leads to a more even distribution of data and queries across the cluster than alternative approaches such as range partitioning.

However, that is not the case in all MySQL Cluster versions so far!
In this post, I’ll do some test cases on MySQL Cluster (of 4 datanodes) to confirm the default sharding key.

Testing on MySQL Cluster 7.2.26 …

As stated in the MySQL Cluster documentation:

Partition.  This is a portion of the data stored by the cluster. There are as many cluster partitions as nodes participating in the cluster. Each node is responsible for keeping at least one copy of any partitions assigned to it (that is, at least one replica) available to the cluster.

According to my understanding for the previous paragraph, if we have a cluster of 6 datanodes we should have 6 partitions for each NDB table. I claim that this is not true for all cases – at least, after the introduction of ndbmtd (Multi-Threaded Daemon) in MySQL Cluster 7.2 .
In this post, I’ll do some …

The original idea of this series was to publish one post per week, but it seems every other week I have some special topic that well deserves a dedicated post. Last week I had no time to complete my writing because of long (and, I hope, useful) Howto post on replacing corrupted partition using non-corrupted one from other server in replication setup. But I had links and notes collected in a draft that I am going to complete now.

First of all, during the previous week I had time to submit two more talks for the  …

This week I've got a question that sounded basically like this:
"Is it possible to just copy the entire partition from the replicated server?"Let me share some background story. As it happens sometimes, user had a huge table with many partitions, let's say hundreds of gigabytes in size each, and one of them got unfortunately corrupted. It happened in a replication setup on master, but lucky they were, they had used innodb_file_per_table=1 and they had a slave that was more or less in sync with master. This allowed to reconfigure replication and continue to work, but the task remained to eventually put master back in use and get correct data in the corrupted partition. Let's assume that dumping and reloading data from one of instances in replication setup is not a desired option, as it will take too much time comparing to just copying the partition tablespace file. Hence the question above...
Side note: Let's assume …