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Mysql：InnoDB Table Compression and InnoDB Page Compression：适用于InnoDB的：表压缩 & 页压缩

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15.9 InnoDB Table and Page Compression

15.9.1 InnoDB Table Compression
15.9.2 InnoDB Page Compression

This section provides information about the InnoDB table compression and InnoDB page compression features. The page compression feature is also referred to as transparent page compression.

Using the compression features of InnoDB, you can create tables where the data is stored in compressed form. Compression can help to improve both raw performance and scalability. The compression means less data is transferred between disk and memory, and takes up less space on disk and in memory. The benefits are amplified for tables with secondary indexes, because index data is compressed also. Compression can be especially important for SSD storage devices, because they tend to have lower capacity than HDD devices.

15.9.1 InnoDB Table Compression

15.9.1.1 Overview of Table Compression
15.9.1.2 Creating Compressed Tables
15.9.1.3 Tuning Compression for InnoDB Tables
15.9.1.4 Monitoring InnoDB Table Compression at Runtime
15.9.1.5 How Compression Works for InnoDB Tables
15.9.1.6 Compression for OLTP Workloads
15.9.1.7 SQL Compression Syntax Warnings and Errors

This section describes InnoDB table compression, which is supported with InnoDB tables that reside in file_per_table tablespaces or general tablespaces. Table compression is enabled using the ROW_FORMAT=COMPRESSED attribute with CREATE TABLE or ALTER TABLE.

15.9.1.1 Overview of Table Compression

Because processors and cache memories have increased in speed more than disk storage devices, many workloads are disk-bound. Data compression enables smaller database size, reduced I/O, and improved throughput, at the small cost of increased CPU utilization. Compression is especially valuable for read-intensive applications, on systems with enough RAM to keep frequently used data in memory.

An InnoDB table created with ROW_FORMAT=COMPRESSED can use a smaller page size on disk than the configured innodb_page_size value. Smaller pages require less I/O to read from and write to disk, which is especially valuable for SSD devices.

The compressed page size is specified through the CREATE TABLE or ALTER TABLE KEY_BLOCK_SIZE parameter. The different page size requires that the table be placed in a file-per-table tablespace or general tablespace rather than in the system tablespace, as the system tablespace cannot store compressed tables. For more information, see Section 15.6.3.2, “File-Per-Table Tablespaces”, and Section 15.6.3.3, “General Tablespaces”.

The level of compression is the same regardless of the KEY_BLOCK_SIZE value. As you specify smaller values for KEY_BLOCK_SIZE, you get the I/O benefits of increasingly smaller pages. But if you specify a value that is too small, there is additional overhead to reorganize the pages when data values cannot be compressed enough to fit multiple rows in each page. There is a hard limit on how small KEY_BLOCK_SIZE can be for a table, based on the lengths of the key columns for each of its indexes. Specify a value that is too small, and the CREATE TABLE or ALTER TABLE statement fails.

In the buffer pool, the compressed data is held in small pages, with a page size based on the KEY_BLOCK_SIZE value. For extracting or updating the column values, MySQL also creates an uncompressed page in the buffer pool with the uncompressed data. Within the buffer pool, any updates to the uncompressed page are also re-written back to the equivalent compressed page. You might need to size your buffer pool to accommodate the additional data of both compressed and uncompressed pages, although the uncompressed pages are evicted from the buffer pool when space is needed, and then uncompressed again on the next access.

15.9.1.2 Creating Compressed Tables

Compressed tables can be created in file-per-table tablespaces or in general tablespaces. Table compression is not available for the InnoDB system tablespace. The system tablespace (space 0, the .ibdata files) can contain user-created tables, but it also contains internal system data, which is never compressed. Thus, compression applies only to tables (and indexes) stored in file-per-table or general tablespaces.

Creating a Compressed Table in File-Per-Table Tablespace

To create a compressed table in a file-per-table tablespace, innodb_file_per_table must be enabled (the default). You can set this parameter in the MySQL configuration file (my.cnf or my.ini) or dynamically, using a SET statement.

After the innodb_file_per_table option is configured, specify the ROW_FORMAT=COMPRESSED clause or KEY_BLOCK_SIZE clause, or both, in a CREATE TABLE or ALTER TABLE statement to create a compressed table in a file-per-table tablespace.

For example, you might use the following statements:

SET GLOBAL innodb_file_per_table=1;
CREATE TABLE t1
 (c1 INT PRIMARY KEY)
 ROW_FORMAT=COMPRESSED
KEY_BLOCK_SIZE=8;
Creating a Compressed Table in a General Tablespace

To create a compressed table in a general tablespace, FILE_BLOCK_SIZE must be defined for the general tablespace, which is specified when the tablespace is created. The FILE_BLOCK_SIZE value must be a valid compressed page size in relation to the innodb_page_size value, and the page size of the compressed table, defined by the CREATE TABLE or ALTER TABLE KEY_BLOCK_SIZE clause, must be equal to FILE_BLOCK_SIZE/1024. For example, if innodb_page_size=16384 and FILE_BLOCK_SIZE=8192, the KEY_BLOCK_SIZE of the table must be 8. For more information, see Section 15.6.3.3, “General Tablespaces”.

The following example demonstrates creating a general tablespace and adding a compressed table. The example assumes a default innodb_page_size of 16K. The FILE_BLOCK_SIZE of 8192 requires that the compressed table have a KEY_BLOCK_SIZE of 8.

mysql> CREATE TABLESPACE `ts2` ADD DATAFILE 'ts2.ibd' FILE_BLOCK_SIZE = 8192 Engine=InnoDB;

mysql> CREATE TABLE t4 (c1 INT PRIMARY KEY) TABLESPACE ts2 ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;
Notes
Restrictions on Compressed Tables

15.9.1.3 Tuning Compression for InnoDB Tables

Most often, the internal optimizations described in InnoDB Data Storage and Compression ensure that the system runs well with compressed data. However, because the efficiency of compression depends on the nature of your data, you can make decisions that affect the performance of compressed tables:

Use the guidelines in this section to help make those architectural and configuration choices. When you are ready to conduct long-term testing and put compressed tables into production, see Section 15.9.1.4, “Monitoring InnoDB Table Compression at Runtime” for ways to verify the effectiveness of those choices under real-world conditions.

When to Use Compression

In general, compression works best on tables that include a reasonable number of character string columns and where the data is read far more often than it is written. Because there are no guaranteed ways to predict whether or not compression benefits a particular situation, always test with a specific workload and data set running on a representative configuration. Consider the following factors when deciding which tables to compress.

Data Characteristics and Compression

A key determinant of the efficiency of compression in reducing the size of data files is the nature of the data itself. Recall that compression works by identifying repeated strings of bytes in a block of data. Completely randomized data is the worst case. Typical data often has repeated values, and so compresses effectively. Character strings often compress well, whether defined in CHAR, VARCHAR, TEXT or BLOB columns. On the other hand, tables containing mostly binary data (integers or floating point numbers) or data that is previously compressed (for example JPEG or PNG images) may not generally compress well, significantly or at all.

You choose whether to turn on compression for each InnoDB table. A table and all of its indexes use the same (compressed) page size. It might be that the primary key (clustered) index, which contains the data for all columns of a table, compresses more effectively than the secondary indexes. For those cases where there are long rows, the use of compression might result in long column values being stored “off-page”, as discussed in DYNAMIC Row Format. Those overflow pages may compress well. Given these considerations, for many applications, some tables compress more effectively than others, and you might find that your workload performs best only with a subset of tables compressed.

To determine whether or not to compress a particular table, conduct experiments. You can get a rough estimate of how efficiently your data can be compressed by using a utility that implements LZ77 compression (such as gzip or WinZip) on a copy of the .ibd file for an uncompressed table. You can expect less compression from a MySQL compressed table than from file-based compression tools, because MySQL compresses data in chunks based on the page size, 16KB by default. In addition to user data, the page format includes some internal system data that is not compressed. File-based compression utilities can examine much larger chunks of data, and so might find more repeated strings in a huge file than MySQL can find in an individual page.

Another way to test compression on a specific table is to copy some data from your uncompressed table to a similar, compressed table (having all the same indexes) in a file-per-table tablespace and look at the size of the resulting .ibd file. For example:

USE test;
SET GLOBAL innodb_file_per_table=1;
SET GLOBAL autocommit=0;

-- Create an uncompressed table with a million or two rows.
CREATE TABLE big_table AS SELECT * FROM information_schema.columns;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
INSERT INTO big_table SELECT * FROM big_table;
COMMIT;
ALTER TABLE big_table ADD id int unsigned NOT NULL PRIMARY KEY auto_increment;

SHOW CREATE TABLE big_table\G

select count(id) from big_table;

-- Check how much space is needed for the uncompressed table.
\! ls -l data/test/big_table.ibd

CREATE TABLE key_block_size_4 LIKE big_table;
ALTER TABLE key_block_size_4 key_block_size=4 row_format=compressed;

INSERT INTO key_block_size_4 SELECT * FROM big_table;
commit;

-- Check how much space is needed for a compressed table
-- with particular compression settings.
\! ls -l data/test/key_block_size_4.ibd

This experiment produced the following numbers, which of course could vary considerably depending on your table structure and data:

-rw-rw----  1 cirrus  staff  310378496 Jan  9 13:44 data/test/big_table.ibd
-rw-rw----  1 cirrus  staff  83886080 Jan  9 15:10 data/test/key_block_size_4.ibd

To see whether compression is efficient for your particular workload:

Database Compression versus Application Compression

Decide whether to compress data in your application or in the table; do not use both types of compression for the same data. When you compress the data in the application and store the results in a compressed table, extra space savings are extremely unlikely, and the double compression just wastes CPU cycles.

Compressing in the Database

When enabled, MySQL table compression is automatic and applies to all columns and index values. The columns can still be tested with operators such as LIKE, and sort operations can still use indexes even when the index values are compressed. Because indexes are often a significant fraction of the total size of a database, compression could result in significant savings in storage, I/O or processor time. The compression and decompression operations happen on the database server, which likely is a powerful system that is sized to handle the expected load.

Compressing in the Application

If you compress data such as text in your application, before it is inserted into the database, You might save overhead for data that does not compress well by compressing some columns and not others. This approach uses CPU cycles for compression and uncompression on the client machine rather than the database server, which might be appropriate for a distributed application with many clients, or where the client machine has spare CPU cycles.

Hybrid Approach

Of course, it is possible to combine these approaches. For some applications, it may be appropriate to use some compressed tables and some uncompressed tables. It may be best to externally compress some data (and store it in uncompressed tables) and allow MySQL to compress (some of) the other tables in the application. As always, up-front design and real-life testing are valuable in reaching the right decision.

Workload Characteristics and Compression

In addition to choosing which tables to compress (and the page size), the workload is another key determinant of performance. If the application is dominated by reads, rather than updates, fewer pages need to be reorganized and recompressed after the index page runs out of room for the per-page “modification log” that MySQL maintains for compressed data. If the updates predominantly change non-indexed columns or those containing BLOBs or large strings that happen to be stored “off-page”, the overhead of compression may be acceptable. If the only changes to a table are INSERTs that use a monotonically increasing primary key, and there are few secondary indexes, there is little need to reorganize and recompress index pages. Since MySQL can “delete-mark” and delete rows on compressed pages “in place” by modifying uncompressed data, DELETE operations on a table are relatively efficient.

For some environments, the time it takes to load data can be as important as run-time retrieval. Especially in data warehouse environments, many tables may be read-only or read-mostly. In those cases, it might or might not be acceptable to pay the price of compression in terms of increased load time, unless the resulting savings in fewer disk reads or in storage cost is significant.

Fundamentally, compression works best when the CPU time is available for compressing and uncompressing data. Thus, if your workload is I/O bound, rather than CPU-bound, you might find that compression can improve overall performance. When you test your application performance with different compression configurations, test on a platform similar to the planned configuration of the production system.

Configuration Characteristics and Compression

Reading and writing database pages from and to disk is the slowest aspect of system performance. Compression attempts to reduce I/O by using CPU time to compress and uncompress data, and is most effective when I/O is a relatively scarce resource compared to processor cycles.

This is often especially the case when running in a multi-user environment with fast, multi-core CPUs. When a page of a compressed table is in memory, MySQL often uses additional memory, typically 16KB, in the buffer pool for an uncompressed copy of the page. The adaptive LRU algorithm attempts to balance the use of memory between compressed and uncompressed pages to take into account whether the workload is running in an I/O-bound or CPU-bound manner. Still, a configuration with more memory dedicated to the buffer pool tends to run better when using compressed tables than a configuration where memory is highly constrained.

Choosing the Compressed Page Size

The optimal setting of the compressed page size depends on the type and distribution of data that the table and its indexes contain. The compressed page size should always be bigger than the maximum record size, or operations may fail as noted in Compression of B-Tree Pages.

Setting the compressed page size too large wastes some space, but the pages do not have to be compressed as often. If the compressed page size is set too small, inserts or updates may require time-consuming recompression, and the B-tree nodes may have to be split more frequently, leading to bigger data files and less efficient indexing.

Typically, you set the compressed page size to 8K or 4K bytes. Given that the maximum row size for an InnoDB table is around 8K, KEY_BLOCK_SIZE=8 is usually a safe choice.

15.9.1.4 Monitoring InnoDB Table Compression at Runtime

Overall application performance, CPU and I/O utilization and the size of disk files are good indicators of how effective compression is for your application. This section builds on the performance tuning advice from Section 15.9.1.3, “Tuning Compression for InnoDB Tables”, and shows how to find problems that might not turn up during initial testing.

To dig deeper into performance considerations for compressed tables, you can monitor compression performance at runtime using the Information Schema tables described in Example 15.1, “Using the Compression Information Schema Tables”. These tables reflect the internal use of memory and the rates of compression used overall.

The INNODB_CMP table reports information about compression activity for each compressed page size (KEY_BLOCK_SIZE) in use. The information in these tables is system-wide: it summarizes the compression statistics across all compressed tables in your database. You can use this data to help decide whether or not to compress a table by examining these tables when no other compressed tables are being accessed. It involves relatively low overhead on the server, so you might query it periodically on a production server to check the overall efficiency of the compression feature.

The INNODB_CMP_PER_INDEX table reports information about compression activity for individual tables and indexes. This information is more targeted and more useful for evaluating compression efficiency and diagnosing performance issues one table or index at a time. (Because that each InnoDB table is represented as a clustered index, MySQL does not make a big distinction between tables and indexes in this context.) The INNODB_CMP_PER_INDEX table does involve substantial overhead, so it is more suitable for development servers, where you can compare the effects of different workloads, data, and compression settings in isolation. To guard against imposing this monitoring overhead by accident, you must enable the innodb_cmp_per_index_enabled configuration option before you can query the INNODB_CMP_PER_INDEX table.

The key statistics to consider are the number of, and amount of time spent performing, compression and uncompression operations. Since MySQL splits B-tree nodes when they are too full to contain the compressed data following a modification, compare the number of “successful” compression operations with the number of such operations overall. Based on the information in the INNODB_CMP and INNODB_CMP_PER_INDEX tables and overall application performance and hardware resource utilization, you might make changes in your hardware configuration, adjust the size of the buffer pool, choose a different page size, or select a different set of tables to compress.

If the amount of CPU time required for compressing and uncompressing is high, changing to faster or multi-core CPUs can help improve performance with the same data, application workload and set of compressed tables. Increasing the size of the buffer pool might also help performance, so that more uncompressed pages can stay in memory, reducing the need to uncompress pages that exist in memory only in compressed form.

A large number of compression operations overall (compared to the number of INSERT, UPDATE and DELETE operations in your application and the size of the database) could indicate that some of your compressed tables are being updated too heavily for effective compression. If so, choose a larger page size, or be more selective about which tables you compress.

If the number of “successful” compression operations (COMPRESS_OPS_OK) is a high percentage of the total number of compression operations (COMPRESS_OPS), then the system is likely performing well. If the ratio is low, then MySQL is reorganizing, recompressing, and splitting B-tree nodes more often than is desirable. In this case, avoid compressing some tables, or increase KEY_BLOCK_SIZE for some of the compressed tables. You might turn off compression for tables that cause the number of “compression failures” in your application to be more than 1% or 2% of the total. (Such a failure ratio might be acceptable during a temporary operation such as a data load).

15.9.1.5 How Compression Works for InnoDB Tables

This section describes some internal implementation details about compression for InnoDB tables. The information presented here may be helpful in tuning for performance, but is not necessary to know for basic use of compression.

Compression Algorithms

Some operating systems implement compression at the file system level. Files are typically divided into fixed-size blocks that are compressed into variable-size blocks, which easily leads into fragmentation. Every time something inside a block is modified, the whole block is recompressed before it is written to disk. These properties make this compression technique unsuitable for use in an update-intensive database system.

MySQL implements compression with the help of the well-known zlib library, which implements the LZ77 compression algorithm. This compression algorithm is mature, robust, and efficient in both CPU utilization and in reduction of data size. The algorithm is “lossless”, so that the original uncompressed data can always be reconstructed from the compressed form. LZ77 compression works by finding sequences of data that are repeated within the data to be compressed. The patterns of values in your data determine how well it compresses, but typical user data often compresses by 50% or more.

Note

InnoDB supports the zlib library up to version 1.2.11, which is the version bundled with MySQL 8.0.

Unlike compression performed by an application, or compression features of some other database management systems, InnoDB compression applies both to user data and to indexes. In many cases, indexes can constitute 40-50% or more of the total database size, so this difference is significant. When compression is working well for a data set, the size of the InnoDB data files (the file-per-table tablespace or general tablespace .ibd files) is 25% to 50% of the uncompressed size or possibly smaller. Depending on the workload, this smaller database can in turn lead to a reduction in I/O, and an increase in throughput, at a modest cost in terms of increased CPU utilization. You can adjust the balance between compression level and CPU overhead by modifying the innodb_compression_level configuration option.

InnoDB Data Storage and Compression

All user data in InnoDB tables is stored in pages comprising a B-tree index (the clustered index). In some other database systems, this type of index is called an “index-organized table”. Each row in the index node contains the values of the (user-specified or system-generated) primary key and all the other columns of the table.

Secondary indexes in InnoDB tables are also B-trees, containing pairs of values: the index key and a pointer to a row in the clustered index. The pointer is in fact the value of the primary key of the table, which is used to access the clustered index if columns other than the index key and primary key are required. Secondary index records must always fit on a single B-tree page.

The compression of B-tree nodes (of both clustered and secondary indexes) is handled differently from compression of overflow pages used to store long VARCHAR, BLOB, or TEXT columns, as explained in the following sections.

Compression of B-Tree Pages

Because they are frequently updated, B-tree pages require special treatment. It is important to minimize the number of times B-tree nodes are split, as well as to minimize the need to uncompress and recompress their content.

One technique MySQL uses is to maintain some system information in the B-tree node in uncompressed form, thus facilitating certain in-place updates. For example, this allows rows to be delete-marked and deleted without any compression operation.

In addition, MySQL attempts to avoid unnecessary uncompression and recompression of index pages when they are changed. Within each B-tree page, the system keeps an uncompressed “modification log” to record changes made to the page. Updates and inserts of small records may be written to this modification log without requiring the entire page to be completely reconstructed.

When the space for the modification log runs out, InnoDB uncompresses the page, applies the changes and recompresses the page. If recompression fails (a situation known as a compression failure), the B-tree nodes are split and the process is repeated until the update or insert succeeds.

To avoid frequent compression failures in write-intensive workloads, such as for OLTP applications, MySQL sometimes reserves some empty space (padding) in the page, so that the modification log fills up sooner and the page is recompressed while there is still enough room to avoid splitting it. The amount of padding space left in each page varies as the system keeps track of the frequency of page splits. On a busy server doing frequent writes to compressed tables, you can adjust the innodb_compression_failure_threshold_pct, and innodb_compression_pad_pct_max configuration options to fine-tune this mechanism.

Generally, MySQL requires that each B-tree page in an InnoDB table can accommodate at least two records. For compressed tables, this requirement has been relaxed. Leaf pages of B-tree nodes (whether of the primary key or secondary indexes) only need to accommodate one record, but that record must fit, in uncompressed form, in the per-page modification log. If innodb_strict_mode is ON, MySQL checks the maximum row size during CREATE TABLE or CREATE INDEX. If the row does not fit, the following error message is issued: ERROR HY000: Too big row.

If you create a table when innodb_strict_mode is OFF, and a subsequent INSERT or UPDATE statement attempts to create an index entry that does not fit in the size of the compressed page, the operation fails with ERROR 42000: Row size too large. (This error message does not name the index for which the record is too large, or mention the length of the index record or the maximum record size on that particular index page.) To solve this problem, rebuild the table with ALTER TABLE and select a larger compressed page size (KEY_BLOCK_SIZE), shorten any column prefix indexes, or disable compression entirely with ROW_FORMAT=DYNAMIC or ROW_FORMAT=COMPACT.

innodb_strict_mode is not applicable to general tablespaces, which also support compressed tables. Tablespace management rules for general tablespaces are strictly enforced independently of innodb_strict_mode. For more information, see Section 13.1.21, “CREATE TABLESPACE Statement”.

Compressing BLOB, VARCHAR, and TEXT Columns

In an InnoDB table, BLOB, VARCHAR, and TEXT columns that are not part of the primary key may be stored on separately allocated overflow pages. We refer to these columns as off-page columns. Their values are stored on singly-linked lists of overflow pages.

For tables created in ROW_FORMAT=DYNAMIC or ROW_FORMAT=COMPRESSED, the values of BLOB, TEXT, or VARCHAR columns may be stored fully off-page, depending on their length and the length of the entire row. For columns that are stored off-page, the clustered index record only contains 20-byte pointers to the overflow pages, one per column. Whether any columns are stored off-page depends on the page size and the total size of the row. When the row is too long to fit entirely within the page of the clustered index, MySQL chooses the longest columns for off-page storage until the row fits on the clustered index page. As noted above, if a row does not fit by itself on a compressed page, an error occurs.

Note

For tables created in ROW_FORMAT=DYNAMIC or ROW_FORMAT=COMPRESSED, TEXT and BLOB columns that are less than or equal to 40 bytes are always stored in-line.

Tables that use ROW_FORMAT=REDUNDANT and ROW_FORMAT=COMPACT store the first 768 bytes of BLOB, VARCHAR, and TEXT columns in the clustered index record along with the primary key. The 768-byte prefix is followed by a 20-byte pointer to the overflow pages that contain the rest of the column value.

When a table is in COMPRESSED format, all data written to overflow pages is compressed “as is”; that is, MySQL applies the zlib compression algorithm to the entire data item. Other than the data, compressed overflow pages contain an uncompressed header and trailer comprising a page checksum and a link to the next overflow page, among other things. Therefore, very significant storage savings can be obtained for longer BLOB, TEXT, or VARCHAR columns if the data is highly compressible, as is often the case with text data. Image data, such as JPEG, is typically already compressed and so does not benefit much from being stored in a compressed table; the double compression can waste CPU cycles for little or no space savings.

The overflow pages are of the same size as other pages. A row containing ten columns stored off-page occupies ten overflow pages, even if the total length of the columns is only 8K bytes. In an uncompressed table, ten uncompressed overflow pages occupy 160K bytes. In a compressed table with an 8K page size, they occupy only 80K bytes. Thus, it is often more efficient to use compressed table format for tables with long column values.

For file-per-table tablespaces, using a 16K compressed page size can reduce storage and I/O costs for BLOB, VARCHAR, or TEXT columns, because such data often compress well, and might therefore require fewer overflow pages, even though the B-tree nodes themselves take as many pages as in the uncompressed form. General tablespaces do not support a 16K compressed page size (KEY_BLOCK_SIZE). For more information, see Section 15.6.3.3, “General Tablespaces”.

Compression and the InnoDB Buffer Pool

In a compressed InnoDB table, every compressed page (whether 1K, 2K, 4K or 8K) corresponds to an uncompressed page of 16K bytes (or a smaller size if innodb_page_size is set). To access the data in a page, MySQL reads the compressed page from disk if it is not already in the buffer pool, then uncompresses the page to its original form. This section describes how InnoDB manages the buffer pool with respect to pages of compressed tables.

To minimize I/O and to reduce the need to uncompress a page, at times the buffer pool contains both the compressed and uncompressed form of a database page. To make room for other required database pages, MySQL can evict from the buffer pool an uncompressed page, while leaving the compressed page in memory. Or, if a page has not been accessed in a while, the compressed form of the page might be written to disk, to free space for other data. Thus, at any given time, the buffer pool might contain both the compressed and uncompressed forms of the page, or only the compressed form of the page, or neither.

MySQL keeps track of which pages to keep in memory and which to evict using a least-recently-used (LRU) list, so that hot (frequently accessed) data tends to stay in memory. When compressed tables are accessed, MySQL uses an adaptive LRU algorithm to achieve an appropriate balance of compressed and uncompressed pages in memory. This adaptive algorithm is sensitive to whether the system is running in an I/O-bound or CPU-bound manner. The goal is to avoid spending too much processing time uncompressing pages when the CPU is busy, and to avoid doing excess I/O when the CPU has spare cycles that can be used for uncompressing compressed pages (that may already be in memory). When the system is I/O-bound, the algorithm prefers to evict the uncompressed copy of a page rather than both copies, to make more room for other disk pages to become memory resident. When the system is CPU-bound, MySQL prefers to evict both the compressed and uncompressed page, so that more memory can be used for “hot” pages and reducing the need to uncompress data in memory only in compressed form.

Compression and the InnoDB Redo Log Files

Before a compressed page is written to a data file, MySQL writes a copy of the page to the redo log (if it has been recompressed since the last time it was written to the database). This is done to ensure that redo logs are usable for crash recovery, even in the unlikely case that the zlib library is upgraded and that change introduces a compatibility problem with the compressed data. Therefore, some increase in the size of log files, or a need for more frequent checkpoints, can be expected when using compression. The amount of increase in the log file size or checkpoint frequency depends on the number of times compressed pages are modified in a way that requires reorganization and recompression.

To create a compressed table in a file-per-table tablespace, innodb_file_per_table must be enabled. There is no dependence on the innodb_file_per_table setting when creating a compressed table in a general tablespace. For more information, see Section 15.6.3.3, “General Tablespaces”.

15.9.1.6 Compression for OLTP Workloads

Traditionally, the InnoDB compression feature was recommended primarily for read-only or read-mostly workloads, such as in a data warehouse configuration. The rise of SSD storage devices, which are fast but relatively small and expensive, makes compression attractive also for OLTP workloads: high-traffic, interactive websites can reduce their storage requirements and their I/O operations per second (IOPS) by using compressed tables with applications that do frequent INSERT, UPDATE, and DELETE operations.

These configuration options let you adjust the way compression works for a particular MySQL instance, with an emphasis on performance and scalability for write-intensive operations:

Because working with compressed data sometimes involves keeping both compressed and uncompressed versions of a page in memory at the same time, when using compression with an OLTP-style workload, be prepared to increase the value of the innodb_buffer_pool_size configuration option.

15.9.1.7 SQL Compression Syntax Warnings and Errors

This section describes syntax warnings and errors that you may encounter when using the table compression feature with file-per-table tablespaces and general tablespaces.

SQL Compression Syntax Warnings and Errors for File-Per-Table Tablespaces

When innodb_strict_mode is enabled (the default), specifying ROW_FORMAT=COMPRESSED or KEY_BLOCK_SIZE in CREATE TABLE or ALTER TABLE statements produces the following error if innodb_file_per_table is disabled.

ERROR 1031 (HY000): Table storage engine for 't1' doesn't have this option
Note

The table is not created if the current configuration does not permit using compressed tables.

When innodb_strict_mode is disabled, specifying ROW_FORMAT=COMPRESSED or KEY_BLOCK_SIZE in CREATE TABLE or ALTER TABLE statements produces the following warnings if innodb_file_per_table is disabled.

mysql> SHOW WARNINGS;
+---------+------+---------------------------------------------------------------+
| Level   | Code | Message                                                       |
+---------+------+---------------------------------------------------------------+
| Warning | 1478 | InnoDB: KEY_BLOCK_SIZE requires innodb_file_per_table.        |
| Warning | 1478 | InnoDB: ignoring KEY_BLOCK_SIZE=4.                            |
| Warning | 1478 | InnoDB: ROW_FORMAT=COMPRESSED requires innodb_file_per_table. |
| Warning | 1478 | InnoDB: assuming ROW_FORMAT=DYNAMIC.                          |
+---------+------+---------------------------------------------------------------+
Note

These messages are only warnings, not errors, and the table is created without compression, as if the options were not specified.

The “non-strict” behavior lets you import a mysqldump file into a database that does not support compressed tables, even if the source database contained compressed tables. In that case, MySQL creates the table in ROW_FORMAT=DYNAMIC instead of preventing the operation.

To import the dump file into a new database, and have the tables re-created as they exist in the original database, ensure the server has the proper setting for the innodb_file_per_table configuration parameter.

The attribute KEY_BLOCK_SIZE is permitted only when ROW_FORMAT is specified as COMPRESSED or is omitted. Specifying a KEY_BLOCK_SIZE with any other ROW_FORMAT generates a warning that you can view with SHOW WARNINGS. However, the table is non-compressed; the specified KEY_BLOCK_SIZE is ignored).

LevelCodeMessage
Warning 1478 InnoDB: ignoring KEY_BLOCK_SIZE=n unless ROW_FORMAT=COMPRESSED.

If you are running with innodb_strict_mode enabled, the combination of a KEY_BLOCK_SIZE with any ROW_FORMAT other than COMPRESSED generates an error, not a warning, and the table is not created.

Table 15.12, “ROW_FORMAT and KEY_BLOCK_SIZE Options” provides an overview the ROW_FORMAT and KEY_BLOCK_SIZE options that are used with CREATE TABLE or ALTER TABLE.

Table 15.12 ROW_FORMAT and KEY_BLOCK_SIZE Options

OptionUsage NotesDescription
ROW_FORMAT=​REDUNDANT Storage format used prior to MySQL 5.0.3 Less efficient than ROW_FORMAT=COMPACT; for backward compatibility
ROW_FORMAT=​COMPACT Default storage format since MySQL 5.0.3 Stores a prefix of 768 bytes of long column values in the clustered index page, with the remaining bytes stored in an overflow page
ROW_FORMAT=​DYNAMIC   Store values within the clustered index page if they fit; if not, stores only a 20-byte pointer to an overflow page (no prefix)
ROW_FORMAT=​COMPRESSED   Compresses the table and indexes using zlib
KEY_BLOCK_​SIZE=n   Specifies compressed page size of 1, 2, 4, 8 or 16 kilobytes; implies ROW_FORMAT=COMPRESSED. For general tablespaces, a KEY_BLOCK_SIZE value equal to the InnoDB page size is not permitted.

Table 15.13, “CREATE/ALTER TABLE Warnings and Errors when InnoDB Strict Mode is OFF” summarizes error conditions that occur with certain combinations of configuration parameters and options on the CREATE TABLE or ALTER TABLE statements, and how the options appear in the output of SHOW TABLE STATUS.

When innodb_strict_mode is OFF, MySQL creates or alters the table, but ignores certain settings as shown below. You can see the warning messages in the MySQL error log. When innodb_strict_mode is ON, these specified combinations of options generate errors, and the table is not created or altered. To see the full description of the error condition, issue the SHOW ERRORS statement: example: 

mysql> CREATE TABLE x (id INT PRIMARY KEY, c INT)

-> ENGINE=INNODB KEY_BLOCK_SIZE=33333;

ERROR 1005 (HY000): Can't create table 'test.x' (errno: 1478)

mysql> SHOW ERRORS;
+-------+------+-------------------------------------------+
| Level | Code | Message                                   |
+-------+------+-------------------------------------------+
| Error | 1478 | InnoDB: invalid KEY_BLOCK_SIZE=33333.     |
| Error | 1005 | Can't create table 'test.x' (errno: 1478) |
+-------+------+-------------------------------------------+

Table 15.13 CREATE/ALTER TABLE Warnings and Errors when InnoDB Strict Mode is OFF

SyntaxWarning or Error ConditionResulting ROW_FORMAT, as shown in SHOW TABLE STATUS
ROW_FORMAT=REDUNDANT None REDUNDANT
ROW_FORMAT=COMPACT None COMPACT
ROW_FORMAT=COMPRESSED or ROW_FORMAT=DYNAMIC or KEY_BLOCK_SIZE is specified Ignored for file-per-table tablespaces unless innodb_file_per_table is enabled. General tablespaces support all row formats. See Section 15.6.3.3, “General Tablespaces”. the default row format for file-per-table tablespaces; the specified row format for general tablespaces
Invalid KEY_BLOCK_SIZE is specified (not 1, 2, 4, 8 or 16) KEY_BLOCK_SIZE is ignored the specified row format, or the default row format
ROW_FORMAT=COMPRESSED and valid KEY_BLOCK_SIZE are specified None; KEY_BLOCK_SIZE specified is used COMPRESSED
KEY_BLOCK_SIZE is specified with REDUNDANT, COMPACT or DYNAMIC row format KEY_BLOCK_SIZE is ignored REDUNDANT, COMPACT or DYNAMIC
ROW_FORMAT is not one of REDUNDANT, COMPACT, DYNAMIC or COMPRESSED Ignored if recognized by the MySQL parser. Otherwise, an error is issued. the default row format or N/A

When innodb_strict_mode is ON, MySQL rejects invalid ROW_FORMAT or KEY_BLOCK_SIZE parameters and issues errors. Strict mode is ON by default. When innodb_strict_mode is OFF, MySQL issues warnings instead of errors for ignored invalid parameters.

It is not possible to see the chosen KEY_BLOCK_SIZE using SHOW TABLE STATUS. The statement SHOW CREATE TABLE displays the KEY_BLOCK_SIZE (even if it was ignored when creating the table). The real compressed page size of the table cannot be displayed by MySQL.

SQL Compression Syntax Warnings and Errors for General Tablespaces

innodb_strict_mode is not applicable to general tablespaces. Tablespace management rules for general tablespaces are strictly enforced independently of innodb_strict_mode. For more information, see Section 13.1.21, “CREATE TABLESPACE Statement”.

For more information about using compressed tables with general tablespaces, see Section 15.6.3.3, “General Tablespaces”.


15.9.2 InnoDB Page Compression

InnoDB supports page-level compression for tables that reside in file-per-table tablespaces. This feature is referred to as Transparent Page Compression. Page compression is enabled by specifying the COMPRESSION attribute with CREATE TABLE or ALTER TABLE. Supported compression algorithms include Zlib and LZ4.

Supported Platforms

Page compression requires sparse file and hole punching support. Page compression is supported on Windows with NTFS, and on the following subset of MySQL-supported Linux platforms where the kernel level provides hole punching support:

Note

All of the available file systems for a given Linux distribution may not support hole punching.

How Page Compression Works

When a page is written, it is compressed using the specified compression algorithm. The compressed data is written to disk, where the hole punching mechanism releases empty blocks from the end of the page. If compression fails, data is written out as-is.

Hole Punch Size on Linux

On Linux systems, the file system block size is the unit size used for hole punching. Therefore, page compression only works if page data can be compressed to a size that is less than or equal to the InnoDB page size minus the file system block size. For example, if innodb_page_size=16K and the file system block size is 4K, page data must compress to less than or equal to 12K to make hole punching possible.

Hole Punch Size on Windows

On Windows systems, the underlying infrastructure for sparse files is based on NTFS compression. Hole punching size is the NTFS compression unit, which is 16 times the NTFS cluster size. Cluster sizes and their compression units are shown in the following table:

Table 15.14 Windows NTFS Cluster Size and Compression Units

Cluster SizeCompression Unit
512 Bytes 8 KB
1 KB 16 KB
2 KB 32 KB
4 KB 64 KB

Page compression on Windows systems only works if page data can be compressed to a size that is less than or equal to the InnoDB page size minus the compression unit size.

The default NTFS cluster size is 4KB, for which the compression unit size is 64KB. This means that page compression has no benefit for an out-of-the box Windows NTFS configuration, as the maximum innodb_page_size is also 64KB.

For page compression to work on Windows, the file system must be created with a cluster size smaller than 4K, and the innodb_page_size must be at least twice the size of the compression unit. For example, for page compression to work on Windows, you could build the file system with a cluster size of 512 Bytes (which has a compression unit of 8KB) and initialize InnoDB with an innodb_page_size value of 16K or greater.

Enabling Page Compression

To enable page compression, specify the COMPRESSION attribute in the CREATE TABLE statement. For example: 

CREATE TABLE t1 (c1 INT) COMPRESSION="zlib";

You can also enable page compression in an ALTER TABLE statement. However, ALTER TABLE ... COMPRESSION only updates the tablespace compression attribute. Writes to the tablespace that occur after setting the new compression algorithm use the new setting, but to apply the new compression algorithm to existing pages, you must rebuild the table using OPTIMIZE TABLE.

ALTER TABLE t1 COMPRESSION="zlib";
OPTIMIZE TABLE t1;

Disabling Page Compression

To disable page compression, set COMPRESSION=None using ALTER TABLE. Writes to the tablespace that occur after setting COMPRESSION=None no longer use page compression. To uncompress existing pages, you must rebuild the table using OPTIMIZE TABLE after setting COMPRESSION=None.

ALTER TABLE t1 COMPRESSION="None";
OPTIMIZE TABLE t1;

Page Compression Metadata

Page compression metadata is found in the INFORMATION_SCHEMA.INNODB_TABLESPACES table, in the following columns:

Note

On Unix-like systems, ls -l tablespace_name.ibd shows the apparent file size (equivalent to FILE_SIZE) in bytes. To view the actual amount of space allocated on disk (equivalent to ALLOCATED_SIZE), use du --block-size=1 tablespace_name.ibd. The --block-size=1 option prints the allocated space in bytes instead of blocks, so that it can be compared to ls -l output.

Use SHOW CREATE TABLE to view the current page compression setting (Zlib, Lz4, or None). A table may contain a mix of pages with different compression settings.

In the following example, page compression metadata for the employees table is retrieved from the INFORMATION_SCHEMA.INNODB_TABLESPACES table.

# Create the employees table with Zlib page compression

CREATE TABLE employees (
    emp_no      INT             NOT NULL,
    birth_date  DATE            NOT NULL,
    first_name  VARCHAR(14)     NOT NULL,
    last_name   VARCHAR(16)     NOT NULL,
    gender      ENUM ('M','F')  NOT NULL,  
    hire_date   DATE            NOT NULL,
    PRIMARY KEY (emp_no)
) COMPRESSION="zlib";

# Insert data (not shown)
  
# Query page compression metadata in INFORMATION_SCHEMA.INNODB_TABLESPACES
  
mysql> SELECT SPACE, NAME, FS_BLOCK_SIZE, FILE_SIZE, ALLOCATED_SIZE FROM
       INFORMATION_SCHEMA.INNODB_TABLESPACES WHERE NAME='employees/employees'\G
*************************** 1. row ***************************
SPACE: 45
NAME: employees/employees
FS_BLOCK_SIZE: 4096
FILE_SIZE: 23068672
ALLOCATED_SIZE: 19415040

Page compression metadata for the employees table shows that the apparent file size is 23068672 bytes while the actual file size (with page compression) is 19415040 bytes. The file system block size is 4096 bytes, which is the block size used for hole punching.

Identifying Tables Using Page Compression

To identify tables for which page compression is enabled, you can query the INFORMATION_SCHEMA.TABLES CREATE_OPTIONS column for tables defined with the COMPRESSION attribute:

mysql> SELECT TABLE_NAME, TABLE_SCHEMA, CREATE_OPTIONS FROM INFORMATION_SCHEMA.TABLES 
       WHERE CREATE_OPTIONS LIKE '%COMPRESSION=%';
+------------+--------------+--------------------+
| TABLE_NAME | TABLE_SCHEMA | CREATE_OPTIONS     |
+------------+--------------+--------------------+
| employees  | test         | COMPRESSION="zlib" |
+------------+--------------+--------------------+

SHOW CREATE TABLE also shows the COMPRESSION attribute, if used.

Page Compression Limitations and Usage Notes

 

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来源： https://www.cnblogs.com/jinzhenshui/p/12504319.html