Or I could place in the title – “Yes, we done it!”

After reaching 500K QPS in Read-Only on SQL queries, it was natural to expect a much higher performance level from InnoDB Memcached Plugin which is by-passing all SQL related layers.. However the story is not simple, and yet far from finished

While for today we have already our first “preview” results showing that we’re able to reach over 1,000,000 Query/sec level with the latest MySQL 5.7 code:

click here to read the full article..

In MySQL 5.6 InnoDB has a dedicated thread (page_cleaner) that’s responsible for performing flushing operations. Page_cleaner performs flushing of the dirty pages from the buffer pool based on two factors:
- access pattern  -  the least recently used pages will be flushed by LRU flusher from LRU_list when buffer pool has no free pages anymore;
- age – the oldest modified non-flushed pages are part of flush_list structure and will be flushed by flush_list flusher based on several heuristics.

There is a good overview of the page_cleaner and also here you may find some details about flushing in MySQL 5.6. Below I describe several additional aspects of the flush_list flushing that was not really …

MySQL 5.6 introduced a new feature called extended secondary keys. We get a lot of questions about it and find that most of them come from a few incorrect assumption. In this post I'll try to get rid of the confusion once and for all. Famous last words... here goes:

Q1: Do I need to do anything to enable extended secondary keys?

No, nothing at all. It's on by default and I can't see any sensible reason why you would want to disable it. However, it is possible to disable it by tuning the optimizer_switch: SET optimizer_switch='use_index_extensions={on|off}'.

Q2: Does extended secondary keys only work with InnoDB?

No, it should work with any storage engine that uses the primary key columns as reference to the row, which means most storage engines with clustered primary keys. I say "should" because it requires a minimum of work from the storage engine provider; it …

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 …

Since introducing TokuMX, we’ve discussed benefits that TokuMX has for existing MongoDB applications that require no changes. In this post, I introduce an extension we’ve made to the indexing API: clustering indexes, a tool that can tremendously improve query performance. If I were to speak to someone about clustering indexes, I think the conversation could go something like this…

What is a Clustering Index?

A clustering index is an index that stores the entire document, not just the defined key.

A common example is …

At MySQL Connect 2013, I talked about how we used MySQL 5.6 at Facebook, and explained some of new features we added to our Facebook MySQL 5.6 source tree. In this post, I'm going to talk about how we made full table scan faster in InnoDB.

Faster full table scan in InnoDB  In general, almost all queries from applications are using indexes, and reading very few rows (0..1 on primary key lookups and 0..hundreds on range scans). But sometimes we run full table scans. Typical full table scan examples are logical backups (mysqldump) and online schema changes (SELECT ... INTO OUTFILE).

 We take logical backups by mysqldump at Facebook. As you know MySQL offers both physical and logical backup commands/utilities. Logical backup has some advantages against physical backup. For example:

• Logical backup size is much smaller. …

The cost of SSDs has been dropping rapidly, and at the time of this writing, 2.5-drives have reached the 1TB capacity mark.  You can actually get inexpensive drives for as little as 60 cents per GB. Even inexpensive SSDs can perform tens of thousands of IOPs and come with 1.5M – 2M hous MTBF and a 5-year warranty: check out the Intel SC S3500 specs as an example. There is however one important factor you need to take into account when considering  SSDs as opposed to conventional hard drives – Write Endurance.

Many of us have heard about SSDs having limits in terms of how many writes SSDs can handle, many however assume this is what is already accounted for in the warranty period and so if the hard drives claim to have sequential write speed of 450MB/sec and a warranty of 5 years we expect …

It all started with a goal to make InnoDB temporary tables more effective. Temporary table semantics are blessed with some important characteristics that can help us simplify lot of operations.

• Temporary tables are not visible across connections
• Temporary tables lifetime is limited to connection lifetime (unless user explicitly drops it).

What does this means in to InnoDB ?

• REDO logging can be avoided for temporary tables and related objects since temporary tables do not survive a shutdown or crash.
• Temporary table definitions can be maintained in-memory without persisting to the disk.
• Locking constraints can be relaxed since only one client can see these tables.
• Change buffering can be avoided since the majority of temporary tables are short-lived.

In order to implement these changes in InnoDB we took a bit different approach:

A quick overview of the InnoDB performance improvements for both read-only and read-write loads.