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8.10.1 The InnoDB Buffer Pool

InnoDB maintains a storage area called the buffer pool for caching data and indexes in memory. Knowing how the InnoDB buffer pool works, and taking advantage of it to keep frequently accessed data in memory, is an important aspect of MySQL tuning.


For additional information about the InnoDB buffer pool, see Section 14.3.3, “InnoDB Buffer Pool Configuration”.


Ideally, you set the size of the buffer pool to as large a value as practical, leaving enough memory for other processes on the server to run without excessive paging. The larger the buffer pool, the more InnoDB acts like an in-memory database, reading data from disk once and then accessing the data from memory during subsequent reads. The buffer pool even caches data changed by insert and update operations, so that disk writes can be grouped together for better performance.

Depending on the typical workload on your system, you might adjust the proportions of the parts within the buffer pool. You can tune the way the buffer pool chooses which blocks to cache once it fills up, to keep frequently accessed data in memory despite sudden spikes of activity for operations such as backups or reporting.

With 64-bit systems with large memory sizes, you can split the buffer pool into multiple parts, to minimize contention for the memory structures among concurrent operations. For details, see Section, “Using Multiple Buffer Pool Instances”.

Internal Details

InnoDB manages the pool as a list, using a variation of the least recently used (LRU) algorithm. When room is needed to add a new block to the pool, InnoDB evicts the least recently used block and adds the new block to the middle of the list. This midpoint insertion strategy treats the list as two sublists:

  • At the head, a sublist of new (or young) blocks that were accessed recently.

  • At the tail, a sublist of old blocks that were accessed less recently.

This algorithm keeps blocks that are heavily used by queries in the new sublist. The old sublist contains less-used blocks; these blocks are candidates for eviction.

The LRU algorithm operates as follows by default:

  • 3/8 of the buffer pool is devoted to the old sublist.

  • The midpoint of the list is the boundary where the tail of the new sublist meets the head of the old sublist.

  • When InnoDB reads a block into the buffer pool, it initially inserts it at the midpoint (the head of the old sublist). A block can be read in because it is required for a user-specified operation such as an SQL query, or as part of a read-ahead operation performed automatically by InnoDB.

  • Accessing a block in the old sublist makes it young, moving it to the head of the buffer pool (the head of the new sublist). If the block was read in because it was required, the first access occurs immediately and the block is made young. If the block was read in due to read-ahead, the first access does not occur immediately (and might not occur at all before the block is evicted).

  • As the database operates, blocks in the buffer pool that are not accessed age by moving toward the tail of the list. Blocks in both the new and old sublists age as other blocks are made new. Blocks in the old sublist also age as blocks are inserted at the midpoint. Eventually, a block that remains unused for long enough reaches the tail of the old sublist and is evicted.

By default, blocks read by queries immediately move into the new sublist, meaning they will stay in the buffer pool for a long time. A table scan (such as performed for a mysqldump operation, or a SELECT statement with no WHERE clause) can bring a large amount of data into the buffer pool and evict an equivalent amount of older data, even if the new data is never used again. Similarly, blocks that are loaded by the read-ahead background thread and then accessed only once move to the head of the new list. These situations can push frequently used blocks to the old sublist, where they become subject to eviction.

Configuration Options

Several InnoDB system variables control the size of the buffer pool and let you tune the LRU algorithm:

  • innodb_buffer_pool_size

    Specifies the size of the buffer pool. If your buffer pool is small and you have sufficient memory, making the pool larger can improve performance by reducing the amount of disk I/O needed as queries access InnoDB tables. As of MySQL 5.7.5, the innodb_buffer_pool_size option is dynamic, which allows you to configure buffer pool size without restarting the server. See Section, “Resizing the InnoDB Buffer Pool Online” for more information.

  • innodb_buffer_pool_instances

    Divides the buffer pool into a user-specified number of separate regions, each with its own LRU list and related data structures, to reduce contention during concurrent memory read and write operations. This option takes effect only when you set the innodb_buffer_pool_size to a size of 1 gigabyte or more. The total size you specify is divided among all the buffer pools. For best efficiency, specify a combination of innodb_buffer_pool_instances and innodb_buffer_pool_size so that each buffer pool instance is at least 1 gigabyte.

  • innodb_old_blocks_pct

    Specifies the approximate percentage of the buffer pool that InnoDB uses for the old block sublist. The range of values is 5 to 95. The default value is 37 (that is, 3/8 of the pool).

  • innodb_old_blocks_time

    Specifies how long in milliseconds (ms) a block inserted into the old sublist must stay there after its first access before it can be moved to the new sublist. The default value is 0: A block inserted into the old sublist moves to the new sublist when Innodb has evicted 1/4 of the inserted block's pages from the buffer pool, no matter how soon after insertion the access occurs. If the value is greater than 0, blocks remain in the old sublist until an access occurs at least that many ms after the first access. For example, a value of 1000 causes blocks to stay in the old sublist for 1 second after the first access before they become eligible to move to the new sublist.

Setting innodb_old_blocks_time greater than 0 prevents one-time table scans from flooding the new sublist with blocks used only for the scan. Rows in a block read in for a scan are accessed many times in rapid succession, but the block is unused after that. If innodb_old_blocks_time is set to a value greater than time to process the block, the block remains in the old sublist and ages to the tail of the list to be evicted quickly. This way, blocks used only for a one-time scan do not act to the detriment of heavily used blocks in the new sublist.

innodb_old_blocks_time can be set at runtime, so you can change it temporarily while performing operations such as table scans and dumps:

SET GLOBAL innodb_old_blocks_time = 1000;
... perform queries that scan tables ...
SET GLOBAL innodb_old_blocks_time = 0;

This strategy does not apply if your intent is to warm up the buffer pool by filling it with a table's content. For example, benchmark tests often perform a table or index scan at server startup, because that data would normally be in the buffer pool after a period of normal use. In this case, leave innodb_old_blocks_time set to 0, at least until the warmup phase is complete.

Monitoring the Buffer Pool Using the InnoDB Standard Monitor

The output from the InnoDB Standard Monitor contains several fields in the BUFFER POOL AND MEMORY section that pertain to operation of the buffer pool LRU algorithm:

  • Old database pages: The number of pages in the old sublist of the buffer pool.

  • Pages made young, not young: The number of old pages that were moved to the head of the buffer pool (the new sublist), and the number of pages that have remained in the old sublist without being made new.

  • youngs/s non-youngs/s: The number of accesses to old pages that have resulted in making them young or not. This metric differs from that of the previous item in two ways. First, it relates only to old pages. Second, it is based on number of accesses to pages and not the number of pages. (There can be multiple accesses to a given page, all of which are counted.)

  • young-making rate: Hits that cause blocks to move to the head of the buffer pool.

  • not: Hits that do not cause blocks to move to the head of the buffer pool (due to the delay not being met).

The young-making rate and not rate will not normally add up to the overall buffer pool hit rate. Hits for blocks in the old sublist cause them to move to the new sublist, but hits to blocks in the new sublist cause them to move to the head of the list only if they are a certain distance from the head.

The preceding information from the Monitor can help you make LRU tuning decisions:

  • If you see very low youngs/s values when you do not have large scans going on, that indicates that you might need to either reduce the delay time, or increase the percentage of the buffer pool used for the old sublist. Increasing the percentage makes the old sublist larger, so blocks in that sublist take longer to move to the tail and be evicted. This increases the likelihood that they will be accessed again and be made young.

  • If you do not see a lot of non-youngs/s when you are doing large table scans (and lots of youngs/s), to tune your delay value to be larger.


Per second averages provided in InnoDB Monitor output are based on the elapsed time between the current time and the last time InnoDB Monitor output was printed.

For more information about InnoDB Monitors, see Section 14.14, “InnoDB Monitors”.

The INNODB_BUFFER_POOL_STATS table and InnoDB buffer pool server status variables provide much of the same buffer pool information that is provided by SHOW ENGINE INNODB STATUS output.

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User Comments
  Posted by Scott Simmons on October 5, 2015
I think this may be subjective based on the systems in place, "Ideally, you set the size of the buffer pool to as large a value as practical, leaving enough memory for other processes on the server to run without excessive paging. The larger the buffer pool, the more InnoDB acts like an in-memory database"

Actually the opposite may be true in some scenarios. What if I am running Solaris, OpenSolaris or an OS using a technology such as ZFS? With that I want innodb buffer cache to be as small as possible to allow the underlying FS to cache all operations that this process will require. This is also more efficient as ZFS uses a combination of MFU & MRU lists using an adaptive caching policy. Disk writes are handled by txg's (transaction groups) to batch writes together by the FS as well. LRU is less adaptive therefore less effective.
  Posted by Tomasz Korwel on October 16, 2015
To the contrary - even with ZFS increasing innodb pool and decreasing ZFS arc pool is the way to go since innodb pool has much shorter "code path" to the data in cache hence reducing number of CPU ticks needed to retrieve the data.
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