When storing a large blob containing textual data, consider compressing it first. 当存储一个包含文本数据的大博客时，首先考虑压缩它。Do not use this technique when the entire table is compressed by InnoDB or MyISAM.当整个表由InnoDB或MyISAM压缩时，不要使用此技术。

For a table with several columns, to reduce memory requirements for queries that do not use the BLOB column, consider splitting the BLOB column into a separate table and referencing it with a join query when needed.对于具有多个列的表，为了减少不使用BULB列的查询的内存需求，请考虑将BULB列拆分为单独的表，并在需要时将其引用到联接查询。

Since the performance requirements to retrieve and display a BLOB value might be very different from other data types, you could put the BLOB-specific table on a different storage device or even a separate database instance. 由于检索和显示BLOB值的性能要求可能与其他数据类型非常不同，因此可以将特定于BLOB的表放在不同的存储设备上，甚至放在单独的数据库实例上。For example, to retrieve a BLOB might require a large sequential disk read that is better suited to a traditional hard drive than to an SSD device.例如，检索BLOB可能需要一个大的顺序磁盘读取，这比SSD设备更适合传统硬盘驱动器。

See Section 8.4.2.2, “Optimizing for Character and String Types” for reasons why a binary VARCHAR column is sometimes preferable to an equivalent BLOB column.有关二进制VARCHAR列有时优于等效BLOB列的原因，请参见第8.4.2.2节，“优化字符和字符串类型”。

Rather than testing for equality against a very long text string, you can store a hash of the column value in a separate column, index that column, and test the hashed value in queries. 您可以将列值的散列存储在单独的列中，为该列编制索引，并在查询中测试散列值，而不是对很长的文本字符串进行相等性测试。(Use the MD5() or CRC32() function to produce the hash value.) （使用MD5()或CRC32()函数生成哈希值。）Since hash functions can produce duplicate results for different inputs, you still include a clause AND blob_column = long_string_value in the query to guard against false matches; the performance benefit comes from the smaller, easily scanned index for the hashed values.由于散列函数可以为不同的输入生成重复的结果，因此在查询中仍然包括一个子句AND blob_column = long_string_value，以防止错误匹配；性能优势来自于散列值的较小、易于扫描的索引。