I am doing a review of some DB tables that were created in our project and came across this. The table contains an Identity column (ID) which is the primarykey for the table and a clustered index has been defined using this ID column. But when I look at the SPROC that retrieves records from this table, I see that the ID column is never used in the query and they query the records based on a USERID column (this column is not unique) and there can be multiple records for the same USERID.
So my question is there any advantage/purpose in creating a clustered index when we know that the records wont be queried with that column?
If the IDENTITY column is never used in WHERE and JOIN clauses, or referenced by foreign keys, perhaps USERID should be a clustered primary key. I would question the need for the ID column at all in that case.
The best choice for the clustered index depends much on how the table is queried. If the majority of queries are by USERID, then it should probably be a unique clustered index (or clustered unique constraint) and the ID column non-clustered.
Keep in mind that the clustered index key is implicitly included in all non-clustered indexes as the row locator. The implication is that non-clustered indexes may more likely cover queries and non-clustered index leaf node pages wider as a result.
I would say your table is mis-designed. Someone apparently thought every table needs a primary key and the primary key is the clustered index. Adding a system-generated unique number as an identifier just adds noise if that number isn't used anywhere. Noise in the clustered index is unhelpful, to say the least.
They are different concepts, by the way. A primary key is a data modeling concern, a logical concept. An index is a physical design issue. A SQL DBMS must support primary keys, but need not have any indexes, clustered or no.
If USERID is what is usually used to search the table, it should be in your clustered index. The clustered index need not be unique and need not be the primary key. I would look at the data carefully to see if some combination of USERID and another column (or two, or more) form a unique identifier for the row. If so, I'd make that the primary key (and clustered index), with USERID as the first column. If query analysis showed that many queries use only USERID and nothing else (for existence testing) I might create a separate index just of USERID.
If no combination of columns constitutes a unique identifier, you have logical problem, to wit: what does the row mean? What aspect of the real world does it represent?
A basic tenet of the Relational Model is that elements in a relation (rows in a table) are unique, that each one identifies something. If two rows are identical, they identify the same thing. What does it mean to delete one of them? Is the thing that they both identify still there, or not? If it is, what purpose did the 2nd row serve?
I hope that gives you another way to think about clustered indexes and keys. I wouldn't be surprised if you find other tables that could be improved, too.
Here is one of the definitions I found for clustered Index:
When is a file is organized so that the ordering of data records is
the same as or close to the ordering of data entries in some index, we
say that the index is clustered.
I'm having trouble understanding the above sentence regarding the clustered Indexes. The things I know about clustered index are:
Clustered indexes reorders the way the records are physically stored in the table, so only one clustered index is possible
Clustered index is created on non key attribute
Well for clustered index we have many view to look into
A clustered index is a type of index where the table records are physically re-ordered to match the index.
Clustered indexes are efficient on columns that are searched for a range of values. After the row with first value is found using a clustered index, rows with subsequent index values are guaranteed to be physically adjacent, thus providing faster access for a user query or an application
You also have to understand the Non-Clustered Index
In other words, a clustered index stores the actual data, where a non-clustered index is a pointer to the data. In most DBMSs, you can only have one clustered index per table, though there are systems that support multiple clusters (DB2 being an example).
Like a regular index that is stored unsorted in a database table, a clustered index can be a composite index, such as a concatenation of first name and last name in a table of personal information.
There are several example and explanations. And this is What do Clustered and Non clustered index actually mean? one of them.
I have a database where all tables include a Site column (char(4)) and a PrimaryId column (int).
Currently the clustered index on all tables is the combination of these two columns. Many customers only have one site so in those cases I think it definitely makes sense to change the clustered index to only include the PrimaryId.
In cases where there are multiple sites though, I'm wondering whether it would still be advantageous to only use the PrimaryId as the clustered index? Might having a smaller clustered index produce better performance than having a unique one?
In case it's relevant, there are generally not going to be more than a few sites. 10 sites would be a lot.
The answer is simple UNIQUE index is always better then NON-UNIQUE. There is some maths behind it but the greater uniqueness is the faster server can look up a record from index.
CLUSTERED index is great as they physically order the records on disk and it always a good idea to use CLUSTERED INDEX on UNIQUE keys.
CLUSTER INDEX with PRIMARY KEY give very good performance with large data. If your data is not high in column then it will not matter much.
I have recently read a article about how nonclustered indexes are matching table rows. I will try to summarize what I believe is relevant to your question.
There are two types of tables (in the context of indexes):
heap - a table without clustered index
clustered index - a table with clustered index
In the first case a nonclustered index is matching rows using RIP-Based bookmarks which has the following format:
file number - page number - row number
and a nonclustered index is looking like this:
You can see the RIP bookmark is in red.
Generally speaking, the rows of a heap do not move; once they have
been inserted into a page they remain on that page. To be more
technically-precise: rows in a heap seldom move, and when they do
move, they leave a forwarding address at the old location. The rows of
a clustered index, however, can move; that is, they can be relocated
to another page during data modification or index reorganization.
In the second the nonclustered index is using the index key of the clustered index as a bookmark and the clustered index itself should meet several criteria:
it must be unique
it should be short
it should be static
I am going to describe the first criteria (the others are described in the link below):
Each index entry bookmark must allow SQL Server to find the one row in
the table that corresponds to that entry. If you create a clustered
index that is not unique, SQL Server will make the clustered index
unique by generating an additional value that "breaks the tie" for
duplicate keys. This extra value is generated by SQL Server to create
uniqueness is called the uniquifier and is transparent to any client
application. You should carefully consider whether or not to allow
duplicates in a clustered index, for the following reasons:
Generating uniquifiers is extra overhead. SQL Server must decide, at
insert time, if a new row's key is a duplicate of an existing row's
key; and, if so, generate a uniquifier values to add to the new row
The uniquifier is a meaningless piece of information; a meaningless
piece of information that is being propagated into the table's
nonclustered indexes. It's usually better to propagate a meaningful
piece of information into the nonclustered indexes.
The whole article can be found here.
A clustered index stores the actual data rows at the leaf level of the index. Returning to the example above, that would mean that the entire row of data associated with the primary key value of 123 would be stored in that leaf node.
Question - in case the primary key does not exists and I set the Name column as clustered index. In this case, will the above statement becomes contradictory?
No - why?
The clustered index will still store the actual data pages at its leaf level, (initially) physically sorted by the name column.
The index navigation structure above the leaf level will contain the name column values for all rows.
So overall: nothing changes.
The primary key is a logical construct, designed to uniquely identify each row in your table. That's why it has to be unique and non-null.
The clustering index is a physical construct that will (initially) phyiscally sort your data by the clustering key and arrange the SQL Server pages accordingly.
While in SQL Server, the primary is used by default as the clustering key, the two do not have to fall together - nor does one have to exist with the other. You can have a table with a non-clustered primary key, or a clustered table without primary key. Both is possible. Whether it's sensible to have that is another discussion - but it's technically possible.
Update: if your primary key is your clustering key, uniqueness is guaranteed (since the primary key must be unique). If you're choosing some column that is not the primary key as your clustering key, and that column does not guarantee uniqueness, SQL Server will - behind the scenes - add a 4-byte (INT) uniqueifier column to those duplicates values to make them unique. So you might have Smith, Smith1, Smith2 and so forth in your clustered index navigation structure for your Smith's.
See:
MSDN: Clustering Index Design Guidelines
Simple-Talk: Effective Clustered Indexes
If the clustered index is not unique, SQL Server creates a 4-byte uniqueifier and adds it to the clustered index value. The uniqueifier is added only if the clustered index value is duplicate, not for all clustered index values.
All nonclustered indexes will contain this value in its leaf level, and non-unique nonclustered index will also have this uniqueifier value in its non-leaf level entry, as a part of bookmark.
Difference between a Primary key and a unique index (or constraint) is that Null values are not allowed in a the primary key column. There is no need to have a primary key on a table but it make things easier for external application to edit the rows in the table and even then, it's not really a necessity with most external applications.
In term of performance, this change nothing. The important is the presence or absence of indexes (either unique or not, clustered or not and with null values or not) and the primary key is essentially simply one more unique index without null value.
For the clustered index, the column doesn't need to be unique and/or without null. A column with duplicates and null values is fine for creating a clustered index.
For a foreign key, it must reference a column with a unique index on it but not necessarily a primary key or without null value. It's perfectly legal to reference a column that is not a primary key and is allowing null value a long as there is a unique index on it. Notice that because there must be an unique index on it, this column cannot have more than a single null value.
There is no limitation on the foreign key column itself (the column on the foreign table) but performance wise, setting an index on it is often a good thing.
I have a limited exposure to DB and have only used DB as an application programmer. I want to know about Clustered and Non clustered indexes.
I googled and what I found was :
A clustered index is a special type of index that reorders the way
records in the table are physically
stored. Therefore table can have only
one clustered index. The leaf nodes
of a clustered index contain the data
pages. A nonclustered index is a
special type of index in which the
logical order of the index does not
match the physical stored order of
the rows on disk. The leaf node of a
nonclustered index does not consist of
the data pages. Instead, the leaf
nodes contain index rows.
What I found in SO was What are the differences between a clustered and a non-clustered index?.
Can someone explain this in plain English?
With a clustered index the rows are stored physically on the disk in the same order as the index. Therefore, there can be only one clustered index.
With a non clustered index there is a second list that has pointers to the physical rows. You can have many non clustered indices, although each new index will increase the time it takes to write new records.
It is generally faster to read from a clustered index if you want to get back all the columns. You do not have to go first to the index and then to the table.
Writing to a table with a clustered index can be slower, if there is a need to rearrange the data.
A clustered index means you are telling the database to store close values actually close to one another on the disk. This has the benefit of rapid scan / retrieval of records falling into some range of clustered index values.
For example, you have two tables, Customer and Order:
Customer
----------
ID
Name
Address
Order
----------
ID
CustomerID
Price
If you wish to quickly retrieve all orders of one particular customer, you may wish to create a clustered index on the "CustomerID" column of the Order table. This way the records with the same CustomerID will be physically stored close to each other on disk (clustered) which speeds up their retrieval.
P.S. The index on CustomerID will obviously be not unique, so you either need to add a second field to "uniquify" the index or let the database handle that for you but that's another story.
Regarding multiple indexes. You can have only one clustered index per table because this defines how the data is physically arranged. If you wish an analogy, imagine a big room with many tables in it. You can either put these tables to form several rows or pull them all together to form a big conference table, but not both ways at the same time. A table can have other indexes, they will then point to the entries in the clustered index which in its turn will finally say where to find the actual data.
In SQL Server, row-oriented storage both clustered and nonclustered indexes are organized as B trees.
(Image Source)
The key difference between clustered indexes and non clustered indexes is that the leaf level of the clustered index is the table. This has two implications.
The rows on the clustered index leaf pages always contain something for each of the (non-sparse) columns in the table (either the value or a pointer to the actual value).
The clustered index is the primary copy of a table.
Non clustered indexes can also do point 1 by using the INCLUDE clause (Since SQL Server 2005) to explicitly include all non-key columns but they are secondary representations and there is always another copy of the data around (the table itself).
CREATE TABLE T
(
A INT,
B INT,
C INT,
D INT
)
CREATE UNIQUE CLUSTERED INDEX ci ON T(A, B)
CREATE UNIQUE NONCLUSTERED INDEX nci ON T(A, B) INCLUDE (C, D)
The two indexes above will be nearly identical. With the upper-level index pages containing values for the key columns A, B and the leaf level pages containing A, B, C, D
There can be only one clustered index per table, because the data rows
themselves can be sorted in only one order.
The above quote from SQL Server books online causes much confusion
In my opinion, it would be much better phrased as.
There can be only one clustered index per table because the leaf level rows of the clustered index are the table rows.
The book's online quote is not incorrect but you should be clear that the "sorting" of both non clustered and clustered indices is logical, not physical. If you read the pages at leaf level by following the linked list and read the rows on the page in slot array order then you will read the index rows in sorted order but physically the pages may not be sorted. The commonly held belief that with a clustered index the rows are always stored physically on the disk in the same order as the index key is false.
This would be an absurd implementation. For example, if a row is inserted into the middle of a 4GB table SQL Server does not have to copy 2GB of data up in the file to make room for the newly inserted row.
Instead, a page split occurs. Each page at the leaf level of both clustered and non clustered indexes has the address (File: Page) of the next and previous page in logical key order. These pages need not be either contiguous or in key order.
e.g. the linked page chain might be 1:2000 <-> 1:157 <-> 1:7053
When a page split happens a new page is allocated from anywhere in the filegroup (from either a mixed extent, for small tables or a non-empty uniform extent belonging to that object or a newly allocated uniform extent). This might not even be in the same file if the filegroup contains more than one.
The degree to which the logical order and contiguity differ from the idealized physical version is the degree of logical fragmentation.
In a newly created database with a single file, I ran the following.
CREATE TABLE T
(
X TINYINT NOT NULL,
Y CHAR(3000) NULL
);
CREATE CLUSTERED INDEX ix
ON T(X);
GO
--Insert 100 rows with values 1 - 100 in random order
DECLARE #C1 AS CURSOR,
#X AS INT
SET #C1 = CURSOR FAST_FORWARD
FOR SELECT number
FROM master..spt_values
WHERE type = 'P'
AND number BETWEEN 1 AND 100
ORDER BY CRYPT_GEN_RANDOM(4)
OPEN #C1;
FETCH NEXT FROM #C1 INTO #X;
WHILE ##FETCH_STATUS = 0
BEGIN
INSERT INTO T (X)
VALUES (#X);
FETCH NEXT FROM #C1 INTO #X;
END
Then checked the page layout with
SELECT page_id,
X,
geometry::Point(page_id, X, 0).STBuffer(1)
FROM T
CROSS APPLY sys.fn_PhysLocCracker( %% physloc %% )
ORDER BY page_id
The results were all over the place. The first row in key order (with value 1 - highlighted with an arrow below) was on nearly the last physical page.
Fragmentation can be reduced or removed by rebuilding or reorganizing an index to increase the correlation between logical order and physical order.
After running
ALTER INDEX ix ON T REBUILD;
I got the following
If the table has no clustered index it is called a heap.
Non clustered indexes can be built on either a heap or a clustered index. They always contain a row locator back to the base table. In the case of a heap, this is a physical row identifier (rid) and consists of three components (File:Page: Slot). In the case of a Clustered index, the row locator is logical (the clustered index key).
For the latter case if the non clustered index already naturally includes the CI key column(s) either as NCI key columns or INCLUDE-d columns then nothing is added. Otherwise, the missing CI key column(s) silently gets added to the NCI.
SQL Server always ensures that the key columns are unique for both types of indexes. The mechanism in which this is enforced for indexes not declared as unique differs between the two index types, however.
Clustered indexes get a uniquifier added for any rows with key values that duplicate an existing row. This is just an ascending integer.
For non clustered indexes not declared as unique SQL Server silently adds the row locator into the non clustered index key. This applies to all rows, not just those that are actually duplicates.
The clustered vs non clustered nomenclature is also used for column store indexes. The paper Enhancements to SQL Server Column Stores states
Although column store data is not really "clustered" on any key, we
decided to retain the traditional SQL Server convention of referring
to the primary index as a clustered index.
I realize this is a very old question, but I thought I would offer an analogy to help illustrate the fine answers above.
CLUSTERED INDEX
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.
NON-CLUSTERED INDEX
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.
Of course, nothing would stop the librarian from photocopying all the cards and sorting them in a different order in a separate card catalog. (Typically there were at least two such catalogs: one sorted by author name, and one by title.) In principle, you could have as many of these "non-clustered" indexes as you want.
Find below some characteristics of clustered and non-clustered indexes:
Clustered Indexes
Clustered indexes are indexes that uniquely identify the rows in an SQL table.
Every table can have exactly one clustered index.
You can create a clustered index that covers more than one column. For example: create Index index_name(col1, col2, col.....).
By default, a column with a primary key already has a clustered index.
Non-clustered Indexes
Non-clustered indexes are like simple indexes. They are just used for fast retrieval of data. Not sure to have unique data.
Clustered Index
A clustered index determines the physical order of DATA in a table. For this reason, a table has only one clustered index(Primary key/composite key).
"Dictionary" No need of any other Index, its already Index according to words
Nonclustered Index
A non-clustered index is analogous to an index in a Book. The data is stored in one place. The index is stored in another place and the index has pointers to the storage location. this help in the fast search of data. For this reason, a table has more than 1 Nonclustered index.
"Biology Book" at starting there is a separate index to point Chapter location and At the "END" there is another Index pointing the common WORDS location
A very simple, non-technical rule-of-thumb would be that clustered indexes are usually used for your primary key (or, at least, a unique column) and that non-clustered are used for other situations (maybe a foreign key). Indeed, SQL Server will by default create a clustered index on your primary key column(s). As you will have learnt, the clustered index relates to the way data is physically sorted on disk, which means it's a good all-round choice for most situations.
Clustered Index
A Clustered Index is basically a tree-organized table. Instead of storing the records in an unsorted Heap table space, the clustered index is actually B+Tree index having the Leaf Nodes, which are ordered by the clusters key column value, store the actual table records, as illustrated by the following diagram.
The Clustered Index is the default table structure in SQL Server and MySQL. While MySQL adds a hidden clusters index even if a table doesn't have a Primary Key, SQL Server always builds a Clustered Index if a table has a Primary Key column. Otherwise, the SQL Server is stored as a Heap Table.
The Clustered Index can speed up queries that filter records by the clustered index key, like the usual CRUD statements. Since the records are located in the Leaf Nodes, there's no additional lookup for extra column values when locating records by their Primary Key values.
For example, when executing the following SQL query on SQL Server:
SELECT PostId, Title
FROM Post
WHERE PostId = ?
You can see that the Execution Plan uses a Clustered Index Seek operation to locate the Leaf Node containing the Post record, and there are only two logical reads required to scan the Clustered Index nodes:
|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
Non-Clustered Index
Since the Clustered Index is usually built using the Primary Key column values, if you want to speed up queries that use some other column, then you'll have to add a Secondary Non-Clustered Index.
The Secondary Index is going to store the Primary Key value in its Leaf Nodes, as illustrated by the following diagram:
So, if we create a Secondary Index on the Title column of the Post table:
CREATE INDEX IDX_Post_Title on Post (Title)
And we execute the following SQL query:
SELECT PostId, Title
FROM Post
WHERE Title = ?
We can see that an Index Seek operation is used to locate the Leaf Node in the IDX_Post_Title index that can provide the SQL query projection we are interested in:
|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
Since the associated PostId Primary Key column value is stored in the IDX_Post_Title Leaf Node, this query doesn't need an extra lookup to locate the Post row in the Clustered Index.
Clustered Index
Clustered indexes sort and store the data rows in the table or view based on their key values. These are the columns included in the index definition. There can be only one clustered index per table, because the data rows themselves can be sorted in only one order.
The only time the data rows in a table are stored in sorted order is when the table contains a clustered index. When a table has a clustered index, the table is called a clustered table. If a table has no clustered index, its data rows are stored in an unordered structure called a heap.
Nonclustered
Nonclustered indexes have a structure separate from the data rows. A nonclustered index contains the nonclustered index key values and each key value entry has a pointer to the data row that contains the key value.
The pointer from an index row in a nonclustered index to a data row is called a row locator. The structure of the row locator depends on whether the data pages are stored in a heap or a clustered table. For a heap, a row locator is a pointer to the row. For a clustered table, the row locator is the clustered index key.
You can add nonkey columns to the leaf level of the nonclustered index to by-pass existing index key limits, and execute fully covered, indexed, queries. For more information, see Create Indexes with Included Columns. For details about index key limits see Maximum Capacity Specifications for SQL Server.
Reference: https://learn.microsoft.com/en-us/sql/relational-databases/indexes/clustered-and-nonclustered-indexes-described
Let me offer a textbook definition on "clustering index", which is taken from 15.6.1 from Database Systems: The Complete Book:
We may also speak of clustering indexes, which are indexes on an attribute or attributes such that all of tuples with a fixed value for the search key of this index appear on roughly as few blocks as can hold them.
To understand the definition, let's take a look at Example 15.10 provided by the textbook:
A relation R(a,b) that is sorted on attribute a and stored in that
order, packed into blocks, is surely clusterd. An index on a is a
clustering index, since for a given a-value a1, all the tuples with
that value for a are consecutive. They thus appear packed into
blocks, execept possibly for the first and last blocks that contain
a-value a1, as suggested in Fig.15.14. However, an index on b is
unlikely to be clustering, since the tuples with a fixed b-value
will be spread all over the file unless the values of a and b are
very closely correlated.
Note that the definition does not enforce the data blocks have to be contiguous on the disk; it only says tuples with the search key are packed into as few data blocks as possible.
A related concept is clustered relation. A relation is "clustered" if its tuples are packed into roughly as few blocks as can possibly hold those tuples. In other words, from a disk block perspective, if it contains tuples from different relations, then those relations cannot be clustered (i.e., there is a more packed way to store such relation by swapping the tuples of that relation from other disk blocks with the tuples the doesn't belong to the relation in the current disk block). Clearly, R(a,b) in example above is clustered.
To connect two concepts together, a clustered relation can have a clustering index and nonclustering index. However, for non-clustered relation, clustering index is not possible unless the index is built on top of the primary key of the relation.
"Cluster" as a word is spammed across all abstraction levels of database storage side (three levels of abstraction: tuples, blocks, file). A concept called "clustered file", which describes whether a file (an abstraction for a group of blocks (one or more disk blocks)) contains tuples from one relation or different relations. It doesn't relate to the clustering index concept as it is on file level.
However, some teaching material likes to define clustering index based on the clustered file definition. Those two types of definitions are the same on clustered relation level, no matter whether they define clustered relation in terms of data disk block or file. From the link in this paragraph,
An index on attribute(s) A on a file is a clustering index when: All tuples with attribute value A = a are stored sequentially (= consecutively) in the data file
Storing tuples consecutively is the same as saying "tuples are packed into roughly as few blocks as can possibly hold those tuples" (with minor difference on one talking about file, the other talking about disk). It's because storing tuple consecutively is the way to achieve "packed into roughly as few blocks as can possibly hold those tuples".
Clustered Index:
Primary Key constraint creates clustered Index automatically if no clustered Index already exists on the table. Actual data of clustered index can be stored at leaf level of Index.
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.
Clustered Index - A clustered index defines the order in which data is physically stored in a table. Table data can be sorted in only way, therefore, there can be only one clustered index per table. In SQL Server, the primary key constraint automatically creates a clustered index on that particular column.
Non-Clustered Index - A non-clustered index doesn’t sort the physical data inside the table. In fact, a non-clustered index is stored at one place and table data is stored in another place. This is similar to a textbook where the book content is located in one place and the index is located in another. This allows for more than one non-clustered index per table.It is important to mention here that inside the table the data will be sorted by a clustered index. However, inside the non-clustered index data is stored in the specified order. The index contains column values on which the index is created and the address of the record that the column value belongs to.When a query is issued against a column on which the index is created, the database will first go to the index and look for the address of the corresponding row in the table. It will then go to that row address and fetch other column values. It is due to this additional step that non-clustered indexes are slower than clustered indexes
Differences between clustered and Non-clustered index
There can be only one clustered index per table. However, you can
create multiple non-clustered indexes on a single table.
Clustered indexes only sort tables. Therefore, they do not consume
extra storage. Non-clustered indexes are stored in a separate place
from the actual table claiming more storage space.
Clustered indexes are faster than non-clustered indexes since they
don’t involve any extra lookup step.
For more information refer to this article.