聚集索引: 如果表上不存在聚集索引，主键约束将自动创建聚集索引。聚类索引的实际数据可以存储在索引的叶级。

Non Clustered Index: Actual data of non clustered index is not directly found at leaf node, instead it has to take an additional step to find because it has only values of row locators pointing towards actual data. Non clustered Index can't be sorted as clustered index. There can be multiple non clustered indexes per table, actually it depends on the sql server version we are using. Basically Sql server 2005 allows 249 Non Clustered Indexes and for above versions like 2008, 2016 it allows 999 Non Clustered Indexes per table.

聚集索引

聚类索引决定了表中DATA的物理顺序。因此，一个表只有一个聚集索引(主键/组合键)。

“字典”不需要任何其他索引，它已经根据单词索引

非聚集索引

非聚集索引类似于Book中的索引。数据存储在一个地方。索引存储在另一个位置，并且索引具有指向存储位置的指针。这有助于快速搜索数据。因此，一个表有超过1个非聚集索引。

“生物书”在开头有一个单独的索引指向章节的位置，在“结尾”有另一个索引指向常用单词的位置

我知道这是一个非常古老的问题，但我想我可以提供一个类比来帮助说明上面的答案。

聚集索引

If you walk into a public library, you will find that the books are all arranged in a particular order (most likely the Dewey Decimal System, or DDS). This corresponds to the "clustered index" of the books. If the DDS# for the book you want was 005.7565 F736s, you would start by locating the row of bookshelves that is labeled 001-099 or something like that. (This endcap sign at the end of the stack corresponds to an "intermediate node" in the index.) Eventually you would drill down to the specific shelf labelled 005.7450 - 005.7600, then you would scan until you found the book with the specified DDS#, and at that point you have found your book.

非聚簇索引

But if you didn't come into the library with the DDS# of your book memorized, then you would need a second index to assist you. In the olden days you would find at the front of the library a wonderful bureau of drawers known as the "Card Catalog". In it were thousands of 3x5 cards -- one for each book, sorted in alphabetical order (by title, perhaps). This corresponds to the "non-clustered index". These card catalogs were organized in a hierarchical structure, so that each drawer would be labeled with the range of cards it contained (Ka - Kl, for example; i.e., the "intermediate node"). Once again, you would drill in until you found your book, but in this case, once you have found it (i.e, the "leaf node"), you don't have the book itself, but just a card with an index number (the DDS#) with which you could find the actual book in the clustered index.

当然，没有什么能阻止图书管理员复印所有的卡片，并将它们按不同的顺序分类在一个单独的卡片目录中。(通常至少有两个这样的目录:一个按作者姓名排序，另一个按标题排序。)原则上，您可以拥有任意数量的这些“非聚集”索引。

聚集索引

聚集索引基本上是一个树状组织的表。与将记录存储在未排序的Heap表空间中不同，聚集索引实际上是具有叶子节点(按群集键列值排序)的B+树索引，存储实际的表记录，如下图所示。

在SQL Server和MySQL中，Clustered Index是默认的表结构。即使表没有主键，MySQL也会添加一个隐藏的集群索引，而SQL Server总是在表有主键列时构建一个集群索引。否则，SQL Server将存储为堆表。

聚集索引可以加速按聚集索引键过滤记录的查询，就像通常的CRUD语句一样。由于记录位于叶节点中，因此在根据记录的Primary Key值定位记录时，不需要额外查找额外的列值。

例如，在SQL Server上执行如下SQL查询:

SELECT PostId, Title
FROM Post
WHERE PostId = ? 

您可以看到，执行计划使用群集索引查找操作来定位包含Post记录的叶子节点，并且扫描群集索引节点只需要两个逻辑读取:

|StmtText                                                                             |
|-------------------------------------------------------------------------------------|
|SELECT PostId, Title FROM Post WHERE PostId = @P0                                    |
|  |--Clustered Index Seek(OBJECT:([high_performance_sql].[dbo].[Post].[PK_Post_Id]), |
|     SEEK:([high_performance_sql].[dbo].[Post].[PostID]=[@P0]) ORDERED FORWARD)      | 

Table 'Post'. Scan count 0, logical reads 2, physical reads 0

非聚簇索引

由于聚集索引通常是使用主键列值构建的，如果您想加快使用其他列的查询速度，那么必须添加次要非聚集索引。

二级索引将在它的叶节点中存储主键值，如下图所示:

因此，如果我们在Post表的Title列上创建一个Secondary Index:

CREATE INDEX IDX_Post_Title on Post (Title)

然后执行下面的SQL查询:

SELECT PostId, Title
FROM Post
WHERE Title = ? 

我们可以看到，索引查找操作用于在IDX_Post_Title索引中定位叶子节点，它可以提供我们感兴趣的SQL查询投影:

|StmtText                                                                      |
|------------------------------------------------------------------------------|
|SELECT PostId, Title FROM Post WHERE Title = @P0                              |
|  |--Index Seek(OBJECT:([high_performance_sql].[dbo].[Post].[IDX_Post_Title]),|
|     SEEK:([high_performance_sql].[dbo].[Post].[Title]=[@P0]) ORDERED FORWARD)|

Table 'Post'. Scan count 1, logical reads 2, physical reads 0

由于相关的PostId主键列值存储在IDX_Post_Title叶节点中，因此此查询不需要额外查找来定位聚集索引中的Post行。

下面是聚类索引和非聚类索引的一些特征:

聚集索引

聚集索引是唯一标识SQL表中的行的索引。 每个表只能有一个聚集索引。 可以创建包含多个列的聚集索引。例如:create Index index_name(col1, col2, col.....)。 默认情况下，具有主键的列已经具有聚集索引。

非聚簇索引

非聚集索引类似于简单索引。它们只是用于快速检索数据。不一定有唯一的数据。

一个非常简单的、非技术性的经验法则是，聚集索引通常用于主键(或者至少是唯一的列)，而非聚集索引用于其他情况(可能是外键)。实际上，SQL Server默认会在你的主键列上创建一个聚集索引。正如您将了解到的，聚类索引与数据在磁盘上物理排序的方式有关，这意味着对于大多数情况，它是一个很好的全面选择。