A few months back, Michael wrote about reconnecting orphaned *.ibd files using MySQL 5.6. I will show you the same procedure, this time for partitioned tables. An InnoDB partition is also a self-contained tablespace in itself so you can use the same method described in the previous post.

To begin with, I have an example table with a few orphaned partitions and we will reconnect each partition one by one to the original table.

mysql [localhost] {msandbox} (recovery) > SHOW CREATE TABLE t1 G
*************************** 1. row ***************************
Table: t1
Create Table: CREATE TABLE `t1` (
[...]
KEY `h_date` (`h_date`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1
/*!50100 PARTITION BY RANGE (year(h_date))
(PARTITION p0 VALUES LESS THAN (2006) ENGINE = InnoDB,
PARTITION p1 VALUES LESS THAN (2010) ENGINE = InnoDB,
PARTITION …

The new InnoDB Labs release contains the ability to create and use independent multi-table general tablespaces.

This feature will provide a way to group tables together into tablespaces at a location and filename of your choosing.  Tables using row formats of Redundant, Compact, and Dynamic can be combined together into the same general tablespace. Compressed tables with the same key_block_size can also be combined together.

The SQL syntax for creating an empty general tablespaces is:

CREATE TABLESPACE `tblspace_name` ADD DATAFILE 'tablespace.ibd' [FILE_BLOCK_SIZE=n];

The filename can contain an absolute path or a path relative to the data …

Percona Toolkit’s  pt-table-checksum performs an online replication consistency check by executing checksum queries on the master, which produces different results on replicas that are inconsistent with the master – and the tool pt-table-sync synchronizes data efficiently between MySQL tables.

The tools by default use the CRC32. Other good choices include MD5 and SHA1. If you have installed the FNV_64 user-defined function, pt-table-sync will detect it and prefer to use it, because it is much faster than the built-ins. You can also use …

This year’s MySQL Central at Oracle Open World was an exhilarating experience. In contrast to the previous year’s MySQL Connect events, MySQL have now got their own Central at the main Oracle Open World. In the previous years, we were always short on time and trying to get a lot of sessions into just two days was just to much. This time I could both present sessions, attend sessions by other users, and also to talk to people in the MySQL community: something that I really enjoy and also find very valuable to see where we should be heading.

This year, the “MySQL Fabric Team” representation on MySQL Central was me and Narayanan Venkateswaran, which is heading the sharding solution in MySQL Fabric. Together with the conference, we also released MySQL Fabric 1.5.2 as the GA release of MySQL Fabric 1.5 containing a few new features:

• Server …

While working with different clients I happen to run across very large slow log files from time to time.  While several opinions on how they should be rotated exist. Many of these opinions use log rotate and the flush logs command,  I prefer not to flush my binary logs though. This is why I agree with Ronald Bradford's blog post from years ago on  how to do this.

• http://ronaldbradford.com/blog/the-correct-approach-to-rolling-mysql-logs-2010-02-22/

I have taken it a little further and scripted the steps. The bash script is built with MySQL 5.6 and the mysql_config_editor in mind it can be used on older versions of MySQL as well.

The script …

For some reason, we’ve been getting a lot of issues with ORDER BY optimization recently. The fixes have passed Elena Stepanova’s scrutiny and I’ve pushed them to MariaDB 10.1. Now, MariaDB’s ORDER BY ... LIMIT optimizer:

• Doesn’t make stupid choices when several multi-part keys and potential range accesses are present (MDEV-6402)
• Always uses “range” and (not full “index” scan) when it switches to an index to satisfy ORDER BY … LIMIT (MDEV-6657)
• Tries hard to be smart and use cost/number of records estimates from other parts of the optimizer (MDEV-6384, MDEV-465, MySQL …

MariaDB 5.5.40 was recently released (it is the latest MariaDB 5.5), and is available for download here:

https://downloads.mariadb.org/mariadb/5.5.40/

This is a maintenance release, and so there are not too many big changes of note, just a number of normal bug fixes. However, there are a few items worth mentioning:

• Includes all bugfixes and updates from MySQL 5.5.40 (MySQL 5.5.40 Overview and Highlights)
• XtraDB updated to the version from …

MariaDB 5.5 and then MySQL 5.6 got Index Condition Pushdown (ICP) optimization (initially coded by yours truly). The idea of ICP is simple: after reading the index record, check the part of WHERE condition that can be computed using index columns, and only then read the table record. That way, we avoid reading table rows that don’t satisfy index condition:

It seems apparent that ICP can never make things slower. The WHERE clause has to be checked anyway, and not reading certain records can only make things faster.

That was what I thought, too, until recently Joffrey Michaie observed the contrary “in the wild”: we’ve got a real-world case where using Index Condition Pushdown was slower than not using it: …

In a previous blog post (Importing related MySQL tables into an Excel Data Model using MySQL for Excel) we covered in detail how an Excel Data Model can be created containing tables and their relationships so the data can be analyzed in Excel via a PivotTable. In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0 that allows you to create PivotTables for data imported from MySQL tables, views or stored procedures, or more importantly for the whole Excel Data Model if it is created.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer …

MySQL has information_schema.tables that contain information such as “data_length” or “avg_row_length.” Documentation on this table however is quite poor, making an assumption that those fields are self explanatory – they are not when it comes to tables that employ compression. And this is where inconsistency is born. Lets take a look at the same table containing some highly compressible data using different storage engines that support MySQL compression:

TokuDB:

mysql> select * from information_schema.tables where table_schema='test' G
*************************** 1. row ***************************
TABLE_CATALOG: def
TABLE_SCHEMA: test
TABLE_NAME: comp
TABLE_TYPE: BASE TABLE
ENGINE: TokuDB
VERSION: 10
ROW_FORMAT: tokudb_zlib
TABLE_ROWS: 40960
AVG_ROW_LENGTH: 10003
DATA_LENGTH: 409722880
MAX_DATA_LENGTH: …