- `ERROR 1114 (HY000) the table . is full` with innodb_file_per_table set to autoextend
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- UPDATE 2013-06-03 13:05 EDT
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- How to fix MySQL ERROR 1114 the table is full issue
- Fix MySQL table is full error from the configuration file
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- ERROR 1114 – The table is full
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- Ошибка The table is full
- The table is full — MariaDB
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- UPDATE 2018-02-27 10:10 EDT
`ERROR 1114 (HY000) the table . is full` with innodb_file_per_table set to autoextend
I have a MySQL database that holds a large amount of data (100-200GB — a bunch of scientific measurements). The vast majority of the data is stored in one table Sample . Now I’m creating a slave replica of the database and I wanted to take the advantages of innodb_file_per_table during the process. So I set innodb_file_per_table in my slave configuration and imported the dump of the database. To my surprise, it failed with
ERROR 1114 (HY000) at line 5602: The table ‘Sample’ is full
The file Sample.ibd is currently about 93GB, with more than 600GB free space available on the partition, so it’s not a disk free-space issue. Neither it seems to be hitting any kind of file-system limit (I’m using ext4).
I’d be grateful for any ideas what could be the cause, or what to investigate.
Update: I’m using mysql Ver 14.14 Distrib 5.1.66, for debian-linux-gnu (x86_64) .
2 Answers 2
You said you are using ext4 . File size limit is 16TB. Thus, Sample.ibd should not be full.
You said your innodb_data_file_path is ibdata1:10M:autoextend . Thus, the ibdata1 file itself has no cap to its size except from the OS.
Why is this message coming up at all? Notice the message is «The table . is full», not «The disk . is full». This table full condition is from a logical standpoint. Think about InnoDB. What interactions are going on ?
My guess is InnoDB is attempting to load 93GB of data as a single transaction. Where would the Table is Full message emanate from? I would look at the ibdata1, not in terms its physical size (which you already ruled out), but in terms of what transaction limits are being reached.
What is inside ibdata1 when innodb_file_per_table is enabled and you load new data into MySQL?
- Data Dictionary
- Double Write Buffer
- Safety Net to Prevent Data Corruption
- Helps Bypass OS for Caching
- Insert Buffer (Streamlines Changes to Secondary Indexes)
- Rollback Segments
- Undo Logs
- Click Here to see a Pictorial Representation of ibdata1
My suspicions tell me that the Undo Logs and/or Redo Logs are to blame.
What are these logs? According to the Book
Chapter 10 : «Storage Engines» Page 203 Paragraphs 3,4 say the following:
The InnoDB engine keeps two types of logs: an undo log and a redo log. The purpose of an undo log is to roll back transactions, as well as to display the older versions of the data for queries running in the transaction isolation level that requires it. The code that handles the undo log can be found in storage/innobase/buf/log/log0log.c.
The purpose of the redo log is to store the information to be used in crash recovery. It permits the recovery process to re-execute the transactions that may or may not have completed before the crash. After re-executing those transactions, the database is brought to a consistent state. The code dealing with the redo log can be found in storage/innobase/log/log0recv.c.
There are 1023 Undo Logs inside ibdata1 (See Rollback Segments and Undo Space). Since the undo logs keep copies of data as they appeared before the reload, all 1023 Undo Logs have reached its limit. From another perspective, all 1023 Undo Logs may be dedicated to the one transaction that loads the Sample table.
You are probably saying «I am loading an empty Sample table». How are Undo Logs involved? Before the Sample table was loaded with 93GB of data, it was empty. Representing every row that did not exist must take up some housecleaning space in the Undo Logs. Filling up 1023 Undo Logs seems trivial given the amount of data pouring into ibdata1 . I am not the first person to suspect this:
From the MySQL 4.1 Documentation, note Posted by Chris Calender on September 4 2009 4:25pm :
Note that in 5.0 (pre-5.0.85) and in 5.1 (pre-5.1.38), you could receive the «table is full» error for an InnoDB table if InnoDB runs out of undo slots (bug #18828).
When you create the mysqldump of the Sample table, please use —no-autocommit
This will put an explicit COMMIT; after every INSERT . Then, reload the table.
If this does not work (you are not going to like this), do this
This will make each INSERT have just one row. The mysqldump will be much larger (10+ times bigger) and could take 10 to 100 times longer to reload.
In either case, this will spare the Undo Logs from being inundated.
UPDATE 2013-06-03 13:05 EDT
If the InnoDB system table (a.k.a ibdata1) strikes a filesize limit and Undo Logs cannot be used, you could just add another system tablespace (ibdata2).
I just encountered this situation just two days ago. I updated my old post with what I did: See Database Design — Creating Multiple databases to avoid the headache of limit on table size
In essence, you have to change innodb_data_file_path to accommodate a new system tablespace file. Let me explain how:
On disk (ext3), my client’s server had the following:
The setting was
Note that ibdata2 grew to 2196875759616 which is 2145386484M .
I had to embed the filesize of ibdata2 into innodb_data_file_path and add ibdata3
When I restarted mysqld, it worked:
In 40 hours, ibdata3 grew to 31G. MySQL was once again working.
How to fix MySQL ERROR 1114 the table is full issue
Posted on Nov 23, 2021
Learn how to fix MySQL ERROR 1114 the table is full issue
The MySQL ERROR 1114 can be triggered when you try to perform an INSERT statement on a table.
The following example shows how the error happens when I try to insert data into the users table:
To fix this error, you need to first check the disk space in where your MySQL server is installed and see if the partition is really full.
You can do so by running the df -h command from the Terminal. Here’s an example partitions listed from my server:
If you see any disk on the list with the Use% value reaching around 90% , then you need to check if your mysql is installed on that disk.
Most likely you will have mysql located in /var/www/mysql directory, so you need to make sure the main mounted partition at / has the Use% lower than 80% .
But if you’re Use% values are low like in the example above, then the error is not caused by the disk partition.
You need to check on your MySQL configuration file next.
Fix MySQL table is full error from the configuration file
You need to open your MySQL config file and look at the configuration for innodb_data_file_path .
The default value may be as follows:
The values of innodb_data_file_path option above will create an ibdata1 directory that stores all critical information for your InnoDB -based tables.
The maximum size of data you can store in your InnoDB tables are 256MB as shown in the autoextend:max:256M in the option above.
To resolve the MySQL table is full issue, try increasing the size of your autoextend parameter to 512M like this:
Alternatively, you can also just write autoextend without specifying the maximum size to allow InnoDB tables to grow until the disk size is full:
Once done, save your configuration file and restart your MySQL server:
Try to connect and insert the data into your database table again. It should work this time.
If you’re using the MyISAM engine for your tables, then MySQL permits each MyISAM table to grow up to 256TB by default.
The MyISAM engine limit can still be increased up to 65,536TB if you need to. Check out the official MySQL documentation on table size limits on how to do that.
Good luck resolving the issue! 👍
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ERROR 1114 – The table is full
At XTIVIA, we have encountered the MySQL Error 1114, “table is full” on quite a few occasions. The description for the error is usually misleading as it implies that a table has reached or exceeded a maximum set limitation. Tables utilizing the InnoDB storage engine do have inherent maximums although in these cases, the 64TB limit for InnoDB tables with InnoDB page sizes of 16KB was not the issue.
It is possible to impose user-defined maximums by explicitly defining the variable innodb_data_file_path. For example setting it to a value of ibdata1:10M:autoextend:max:256M will limit the data in InnoDB tables to a total of 256MB. Removing the max:256MB term will eliminate the imposed maximum.
In most cases, ERROR 1114 results from lack of disk space. If a partition, disk, or LUN has been exhausted of all space and MySQL attempts to insert data into the table, it will fail with Error 1114.
One example where this error was encountered was during a backup on a large database. Although there was plenty of disk space available on the partition, as mysqldump began backing up one particularly large table, it sent hundreds of thousands of errors reporting that the table was full. Again, the table was not full as no limits were set and the table was not near the 64TB maximum. The problem was that as mysqldump ran, it was creating a large file on the same partition where the data existed thereby doubling the size required for the table.
Adding more disk space was not an option under the time crunch and the maintenance window available for the client. The issue was resolved by running mysqldump on the table in increments. By adding a “–where” option in the mysqldump command, the backup was run stepwise on smaller chunks of data enabling the backup file and data files to exist in the same partition without running out of space. Given the autoincrement primary key and total number of rows, the table was divided into ten groups by rows to dump separately. Each ran successfully, the errors halted and a successful backup was therefore performed on the entire database.
MySQL reports a “Table is full” error where, in most cases, the issue involves running out of disk space. By default, limits are not imposed on MySQL tables however there are relatively large maximums inherent to the database and those maximums have not been the issue in our experience. If you are seeing this error, first check the disk space on the partition to ensure that this is not the cause of the error. If disk space is not a concern, check the variable innodb_data_file_path to see if a maximum table size has been set explicitly.
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Ошибка The table is full
Существует несколько случаев, когда выдается эта ошибка:
Используется старая версия MySQL (до 3.23.0), а размещенная в памяти временная таблица становится больше, чем tmp_table_size байтов. Для решения этой проблемы можно использовать опцию -O tmp_table_size=# , чтобы mysqld увеличил размер временных таблиц, или опцию SQL SQL_BIG_TABLES , перед тем как выдать сомнительный запрос (Синтаксис команды SET). Можно также запускать mysqld с опцией —big-tables — эффект здесь будет таким же, как и от использования SQL_BIG_TABLES для всех запросов. В версии MySQL 3.23 размещенные в памяти временные таблицы после того, как размер таблицы превысит tmp_table_size , автоматически преобразуются в расположенные на диске таблицы типа MyISAM .
Используются таблицы InnoDB и исчерпалось место в табличном пространстве InnoDB . В таком случае следует увеличить табличное пространство InnoDB .
Используются таблицы ISAM или MyISAM в операционной системе, которая поддерживает файлы размером до 2 Гб, и файл данных или индексный файл достигли этого предела.
Используются таблицы MyISAM , и размер требуемых данных или индекса превышает тот, который предусматривался MySQL при выделении указателей (если MAX_ROWS не указано в CREATE TABLE , MySQL выделяет указатели, предусматривающие размещение только 4 Гб данных). Проверить максимальные размеры данных/индекса можно посредством
или с помощью myisamchk -dv база_данных/таблица . Если проблема связана с указателями, то это можно исправить с помощью команды наподобие следующей:
Указывать AVG_ROW_LENGTH нужно только для таблиц с полями типа BLOB/TEXT , поскольку в этом случае MySQL не может оптимизировать требуемое пространство, исходя только из количества строк.
The table is full — MariaDB
I am getting the following error whist trying to execute a long running query.
1\AppData\Local\Temp#sql1664_349_19be’ is full
The C drive (NTFS) on the server has 135GB free space. The D drive (NTFS) which holds the data has 365GB free out of 800GB.
The server has 32GB RAM.
The query I am running is reasonably simple but it is run against 61 million rows.
I have 18 indexes on tblinvoice and the table is INNODB.
This is my.ini file
EDIT: Updated my.ini with suggested changes to innodb-log-file-size, innodb_log_buffer_size, tmp_table_size, max_heap_table_size,
3 Answers 3
Please do not get fooled by the error message.
Note that the error is table is full . It does not say disk is full .
What would create a table is full condition ?
It has to do with the changes that are pouring into the rollback segments for a transaction.
I have addressed this many times
It appears that one of the following occurred
- The SELECT was in the middle of a transaction
- The SELECT attempted to hold too much rollback info in the face of many transactions
In either case, the tblinvoice table probably had so many changes pending that the SELECT just had to give up. This could have caused all write transactions against tblinvoice to rollback.
If you were running this SELECT on a busy Master with lots of writes against tblinvoice , then I could this SELECT having this problem.
What you should do is set up a reporting slave (running MySQL Replication) and run this type of query on it instead on the main server.
UPDATE 2018-02-27 10:10 EDT
Your problem may be the amount of RAM free.
You currently have this
Try running the query again so that the temp table goes immediately to disk
Keep watch on the C:\Windows\SERVIC
1\AppData\Local folder. Watch the temp file that shows up in that folder. What I am hoping is that the temp table will reach the needed size on disk. Why ?
With tmp_table_size=2G and max_heap_table_size=2G , the temp table has to reach 2G in RAM before transferring to disk. My working theory is that you do not have 2GB of RAM free (We are talking Windows, right . ). This is why I am suggesting lowering these to 16M (which is the default value anyway). Give it a try .