<海量数据库解决方案>2011022101

本文详细解析了表和索引分离型存储结构的概念及其特点,并深入探讨了ROWID、行迁移(Migration)、行链接(Chain)等关键技术。此外,还介绍了聚簇因子(ClusterFactor)的作用及如何通过提升聚簇因子来提高数据读取效率。
【摘抄】

【From数据的存储结构和特征】
1、所谓的表和索引分离型的存储结构其实就是堆表,即用来存储数据的表和为了快速查找特定数据而使用的索引完全作为不同的对象来存储。

堆表最大特点:数据的存储独立性

2、关键字:ROWID、行迁移(Migration)、行链接(Chain)
文中对行迁移和行链接的描述不是特别精确,查询网络资料,来源Oracle官方,如下:
http://download.oracle.com/docs/cd/B19306_01/server.102/b14220/logical.htm#sthref338
In two circumstances, the data for a row in a table may be too large to fit into a single data block. In the first case, the row is too large to fit into one data block when it is first inserted. In this case, Oracle stores the data for the row in a chain of data blocks (one or more) reserved for that segment. Row chaining most often occurs with large rows, such as rows that contain a column of datatype LONG or LONG RAW. Row chaining in these cases is unavoidable.

However, in the second case, a row that originally fit into one data block is updated so that the overall row length increases, and the block's free space is already completely filled. In this case, Oracle migrates the data for the entire row to a new data block, assuming the entire row can fit in a new block. Oracle preserves the original row piece of a migrated row to point to the new block containing the migrated row. The rowid of a migrated row does not change.

When a row is chained or migrated, I/O performance associated with this row decreases because Oracle must scan more than one data block to retrieve the information for the row.

也就是说,行链接(Row Chaining)发生在INSERT阶段数据块无法容纳过大数据时,而行迁移(Row Migrating)发生在UPDATE阶段时原数据块无法容纳增大的数据时。

网络资料地址:http://space.itpub.net/519536/viewspace-624408

3、聚簇因子(Cluster Factor):按照索引列值进行了排序的索引行序和对应表中数据行序的相似程度。

如果表中行的存储顺序与我们经常读取较大范围行的顺序一致,则就能够在很大程度上提高读取效率。{就是说提高聚簇因子,就可能提高读取效率}



转载于:https://www.cnblogs.com/GoGoagg/archive/2011/02/21/1959493.html

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