In SQL server the partitioning have cycle like
Table -> on Partition Schema -> on File Group (f1,f2,f3,f4,....)
For example in Oracle :
A filegroup in SQL Server is similar to tablespaces in Oracle, it is a logical storage for table and index data that can contain one or multiple OS files.
but how about MariaDB does it have File Group ?
Not as such. What are you trying to achieve? Keep in mind that some things like that exist because disks used to be smaller than databases. Today, there is rarely an issue. Furthermore RAID controllers, SANs, etc, eliminate the need (or even the desirability) of manually deciding what file goes where. OS's have ways to concatenate multiple volumes, even on the fly. Etc.
MyISAM has the ability to say where the data goes and where the index file goes. But MyISAM is all but dead. Even there, it was folly to put the data on one drive and the indexes on another. In performing a query, first the index is accessed, then the data. That is little, if any performance was gained. Simple RAID striping is likely to do better.
InnoDB has a way to spell out ibdata1, ibdata2, etc. That dates back to the days when the OS could not make a file bigger than 2GB or 4GB. It is essentially never used today.
InnoDB tables can either be all in ibdata1 or scattered among individual .ibd files. But I don't really think this is what you are talking about. With this "file per table", tiny tables are inefficiently stored. MySQL 8.0 will improve on that slightly by letting you put multiple tables in a given "tablespace", akin to .ibd file.
An InnoDB tablespace contains all the data and indexes for a given table or set of tables. Partitioned tables, when file_per_table, had each partition live in a different .ibd file. This may be changing with 8.0.
All of these are hardly worth noting. I would guess that only 1% of systems need to even think about it. Simply let MySQL/MariaDB do what it wants; it's good enough.
A related thing... In the '80s and '90s some vendors had "raw device" access because they thought they could do better than going through the OS. Again, OS's have improved, RAID controllers are sophisticated, and SANs exist. So raw is no longer important. (I don't think MySQL ever had it.) It's bound to have be a big development and maintenance problem for the vendor.
How many DBAs have put tmpdir in a separate partition, only to find that things are crashing because it was not big enough. Ditto for RAM-disk.
Related
I have largish (InnoDB) tables in a database; apparently the users are capable of making SELECTs with JOINs that result in temporary, large (and thus on-disk) tables. Sometimes, those are so large that they exhaust disk space, leading to all sorts of weird issues.
Is there a way to limit temp table maximum size for an on-disk table, so that the table doesn't overgrow the disk? tmp_table_size only applies to in-memory tables, despite the name. I haven't found anything relevant in the documentation.
There's no option for this in MariaDB and MySQL.
I ran into the same issue as you some months ago, I searched a lot and I finally partially solved it by creating a special storage area on the NAS for themporary datasets.
Create a folder on your NAS or a partition on an internal HDD, it will be by definition limited in size, then mount it, and in the mysql ini, assign the temporary storage to this drive: (choose either windows/linux)
tmpdir="mnt/DBtmp/"
tmpdir="T:\"
mysql service should be restarted after this change.
With this approach, once the drive is full, you still have "weird issues" with on-disk queries, but the other issues are gone.
There was a discussion about an option disk-tmp-table-size, but it looks like the commit did not make it through review or got lost for some other reason (at least the option does not exist in the current code base anymore).
I guess your next best try (besides increasing storage) is to tune MySQL to not make on-disk temp tables. There are some tips for this on DBA. Another attempt could be to create a ramdisk for the storage of the "on-disk" temp tables, if you have enough RAM and only lack disk storage.
While it does not answer the question for MySQL, MariaDB has tmp_disk_table_size and potentially also useful max_join_size settings. However, tmp_disk_table_size is only for MyISAM or Aria tables, not for InnoDB. Also, max_join_size works only on the estimated row count of the join, not the actual row count. On the bright side, the error is issued almost immediately.
Is it OK to keep 10000+ tables in a MySQL database?
I'm making a messaging/chat script, so I'm thinking about partitioning data's over several tables as it will be a huge amount of data after some days.
IS IT OK?
Or it has some effect?
Well, as a table can hold millions of rows so I was thinking maybe a database can hold large number of tables too
or, the question could be like, how does Facebook stores their huge amount of daily chat messages?
I'm a newbie in MySQL, please help
MySQL has no limit on the number of tables. The underlying file system may have a limit on the number of files that represent tables. Individual storage engines may impose engine-specific constraints. InnoDB permits up to 4 billion tables.
Even so, the typical DBMS will 'handle' such large databases, but there is more strain on the system catalog than usual in such systems.
I have about huge tables in one database with no ill effects, other than displaying the table list in phpMyAdmin taking a while
It's possible, but I would avoid it unless you have a really good use case for it. It raises all kinds of scalability and maintainability issues. Your table size is mainly limited by available disk space.
If you really need to do it...
You'll need to increase the maximum number of file descriptors that your OS will allow to have open, since MyISAM tables use two file descriptors per table. (If you're using Linux then read the section about ulimit in the man page for bash for how to do this).
Also, there's a MySQL config value called table_cache that limits the number of allowed tables. You'll need to make sure that's large enough to support the number of tables you need.
You won't want to use the standard "flush tables" anymore (unless you're the kind of person that likes to watch paint dry) so you'll need to flush each table individually (e.g. before shutdown).
Again, I would avoid using so many tables. You're probably better off making your schema support what you need in a handful of tables, and consider archiving, warehousing (or deleting!) old data if you're concerned about storing too much data.
So, one of my tables in MySQL which uses the InnoDB storage engine will contain multi-billion rows(with potentially no limit to how many will be inserted).
Can you tell me what sort of optimizations i can do to help speed up things?
Cause with a few million rows already, it will start getting slow.
Of course if you suggest to use something else. The only options i have are PostgreSQL and Sqlite3. But I've been told that sqlite3 is not a good choice for that.
As for postgresql, i have absolutely no idea how it is, as i've never used it.
I imagine though, at least about 1000-1500 inserts per second in that table.
A simple answer to your question would be yes InnoDB would be the perfect choice for a multi-billion row data set.
There is a host of optimization that is possbile.
The most obvious optimizations would be setting a large buffer pool, as buffer pool is the single most important thing when it comes to InnoDB because InnoDB buffers the data as well as the index in the buffer pool. If you have a dedicated MySQL server with only InnoDB tables, then you should set upto 80% of the available RAM to be used by InnoDB.
Another most important optimization is having proper indexes on the table (keeping in mind the data access/update pattern), both primary and secondary. (Remember that primary indexes are automatically appended to secondary indexes).
With InnoDB there are some extra goodies, such as protection from data corruption, auto-recovery etc.
As for increasing write-performance, you should setup your transaction log files to be upto a total of 4G.
One other thing that you can do is partition the table.
You can eek out more performance, by setting the bin-log-format to "row", and setting the auto_inc_lock_mode to 2 (that will ensure that innodb does not hold table level locks when inserting into auto-increment columns).
If you need any specific advice you can contact me, I would be more than willing to help.
optimizations
Take care not to have too many indexes. They are expensive when inserting
Make your datatypes fit your data, as tight fit you can. (so don't go saving ip-adresses in a text or a blob, if you know what i mean). Look in to varchar vs char. Don't forget that because varchar is more flexible, you are trading in some things. If you know a lot about your data it might help to use char's, or it might be clearly better to use varchars. etc.
Do you read at all from this table? If so, you might want to do all the reading from a replicated slave, although your connection should be good enough for that amount of data.
If you have big inserts (aside from the number of inserts), make sure your IO is actually quick enough to handle the load.
I don't think there is any reason MySQL wouldn't support this. Things that can slow you down from "thousands" to "millions" to "billions" are stuff like aforementioned indexes. There is -as far as i know- no "mysql is full" problem.
Look into Partial indexes. From wikipedia (quickest source I could find, didn't check the references, but I'm sure you can manage:)
MySQL as of version 5.4 does not
support partial indexes.[3] In MySQL,
the term "partial index" is sometimes
used to refer to prefix indexes, where
only a truncated prefix of each value
is stored in the index. This is
another technique for reducing index
size.[4]
No idea on the MySQL/InnoDB part (I'd assume it'll cope). But if you end up looking at alternatives, PostgreSQL can manage a DB of unlimited size on paper. (At least one 32TB database exists according to the FAQ.)
Can you tell me what sort of optimizations i can do to help speed up things?
Your milage will vary depending on your application. But with billions of rows, you're at least looking into partitioning your data, in order to work on smaller tables.
In the case of PostgreSQL, you'd also look into creating partial indexes where appropriate.
You may want to have a look at:
http://www.mysqlperformanceblog.com/2006/06/09/why-mysql-could-be-slow-with-large-tables/
http://forums.whirlpool.net.au/archive/954126
If you have a very large table (Billions of records) and need to data mine the table (queries that read lots of data), mysql can slow to a crawl.
Large databases (200+GB) are fine, but they are bound by IO/ temp table to disk and multiple other issues when attempting to read large groups that don't fit in memory.
We're running a social networking site that logs every member's action (including visiting other member's pages); this involves a lot of writes to the db. These actions are stored in a MyISAM table and since something is starting to tax the CPU, my first thought was that it's the table locking of MyISAM that is causing this stress on the CPU.
There are only reads and writes, no updates to this table. I think the balance between reads and writes is about 50/50 for this table, would InnoDB therefore be a better option?
If I want to change the table to InnoDB and we don't use foreign key constraints, transactions or fulltext indexes - do I need to worry about anything?
Notwithstanding any benefits / drawbacks of its use, which are discussed in other threads ( MyISAM versus InnoDB ), migration is a nontrivial process.
Consider
Functionally testing all components which talk to the database if possible - difference engines have different semantics
Running as much performance testing as you can - some things may improve, others may be much worse. A well-known example is SELECT COUNT(*) on a large table.
Checking that all your code will handle deadlocks gracefully - you can get them without explicit use of transactions
Estimate how much space usage you'll get by converting - test this in a non-production environment.
You will doubtless need to change things in a large software platform; this is ok, but seeing as you (hopefully) have a lot of auto-test coverage, change should be acceptable.
PS: If "Something is starting to tax the CPU", then you should a) Find out what, in a non-production environment, b) Try various options to reduce it, in a non-production environment. You should not blindly start doing major things like changing database engines when you haven't fully analysed the problem.
All performance testing should be done in a non-production environment, with production-like data and on production-grade hardware. Otherwise it is difficult to interpret results correctly.
With regards to other potential migration problems:
1) Space - InnoDB tables often require more disk space, though the Barracuda file format for new versions of InnoDB have narrowed the difference. You can get a sense for this by converting a recent backup of the tables and comparing the size. Use "show table status" to compare the data length.
2) Full text search - only on MyISAM
3) GIS/Spatial datatypes - only on MyISAM
On performance, as the other answers and the referenced answer indicate, it depends on your workload. MyISAM is much faster for full table scans. InnoDB tends to be much faster for highly concurrent access. InnoDB can also be much faster if your lookups are based on the primary key.
Another performance issue is that MyISAM can always keep a row count, since it only does table level locking. So, if you're frequently trying to get the row count for a very large table, it may be much slower with InnoDB. Search the Internet if you need a workaround for this, as I've seen several proposed.
Depending on the size of the table(s), you may also need to update your MySQL config file. At the very least, you may want to shift bytes from key_buffer to innodb_buffer_pool_size. You won't get a fair comparison if you leave the database as being optimized for MyISAM. Read up on all the innodb_* configuration properties.
I think it's quite possible that switching to InnoDB would improve performance, but In my experience, you can't really be sure until you try it. If I were you, I would set up a test environment on the same server, convert to InnoDB and run a benchmark.
From my experience, MyISAM tables are only useful for text indexing where you need good performance with searches on big text, but you still don't need a full fledged search engine like Solr or ElasticSearch.
If you want to switch to InnoDB but want to keep indexing your text in a MyISAM table, I suggest you take a look at this: http://blog.lavoie.sl/2013/05/converting-myisam-to-innodb-keeping-fulltext.html
Also: InnoDB supports live atomic backups using innobackupex from Percona. This is godsent when dealing with production servers.
Microsoft SQL Server has a nice feature, which allows a database to be automatically expanded when it becomes full. In MySQL, I understand that a database is, in fact, a directory with a bunch of files corresponding to various objects. Does it mean that a concept of database size is not applicable and a MySQL database can be as big as available disk space allows without any additional concern? If yes, is this behavior the same across different storage engines?
It depends on the engine you're using. A list of the ones that come with MySQL can be found here.
MyISAM tables have a file per table. This file can grow to your file system's limit. As a table gets larger, you'll have to tune it as there's index and data size optimizations that limit the default size. Also, this MyISAM documentation page says:
There is a limit of 2^32 (~4.295E+09)
rows in a MyISAM table. If you build
MySQL with the --with-big-tables
option, the row limitation is
increased to (2^32)^2 (1.844E+19) rows.
See Section 2.16.2, “Typical configure
Options”. Binary distributions for
Unix and Linux are built with this
option.
InnoDB can operate in 3 different modes: using innodb table files, using a whole disk as a table file or using innodb_file_per_table.
Table files are pre-created per your MySQL instance. You typically create a large amount of space and monitor it. When it starts filling up, you need to configure another file and restart your server. You can also set it to autoextend, so that it will add a chunk of space to the last table file when it starts to fill up. I typically don't use this feature, as you never know when you'll take the performance hit for extending the table. This page talks about configuring it.
I've never used a whole disk as a table file, but it can be done. Instead of pointing to a file, I believe you point your InnoDB table files at the un-formatted, unmounted device.
innodb_file_per_table makes InnoDB tables act like MyISAM tables. Each table gets its own table file. Last time I used this, the table files did not shrink if you deleted rows from them. When a table is dropped or altered, the file resizes.
The Archive engine is a gzipped MyISAM table.
A memory table doesn't use disk at all. In fact, when a server restarts, all the data is lost.
Merge tables are like a poor man's partitioning for MyISAM tables. It causes a bunch of identical tables to be queried as if there were one. Aside from the FRM table definition, no files exist other than the MyISAM ones.
CSV tables are wrappers around CSV files. The usual file system limits apply here. They are not too fast, since they can't have indexes.
I don't think anyone uses BDB any more. At least, I've never used it. It uses a Berkly database as a back end. I'm not familiar with its restrictions.
Federated tables are used to connect to and query tables on other database servers. Again, there is only an FRM file.
The Blackhole engine doesn't store anything locally. It's used primarily for creating replication logs and not for actual data storage, since there is no data storage :)
MySQL Cluster is completely different: it stores just about everything in memory (recent editions allow disk storage) and is very different from all the other engines.
what you describe is roughly true for MyISAM tables. for InnoDB tables the picture is different, and more similar to what other DBMSs do: one (or a few) big file with complex internal structure for the whole server. to optimize it, you can use a whole disk (or partition) as a file. (at least in unix-like systems, where everything is a file)