If you know only one thing about clustered index is that : it is default on primary key and behave like a primary key i.e. it will not allow null values, duplicate values then you have to update yourself. If the clustered index is created on the primary key then it will behave like the primary key but once you remove the primary key and only clustered index left then it will accept null values and duplicates also.
Try the below case:
create a table without primary key and create a simple clustered index on one column and then create a primary key on the other column and see the difference now. Its on you, try and find the answer.
A clustered index determines the physical order of data in a table. A clustered index is analogous to a telephone directory, which arranges data by last name. Because the clustered index dictates the physical storage order of the data in the table, a table can contain only one clustered index. However, the index can comprise multiple columns (a composite index), like the way a telephone directory is organized by last name and first name. A clustered index is particularly efficient on columns that are often searched for ranges of values. After the row with the first value is found using the clustered index, rows with subsequent indexed values are guaranteed to be physically adjacent. For example, if an application frequently executes a query to retrieve records between a range of dates, a clustered index can quickly locate the row containing the beginning date, and then retrieve all adjacent rows in the table until the last date is reached. This can help increase the performance of this type of query. Also, if there is a column(s) that is used frequently to sort the data retrieved from a table, it can be advantageous to cluster (physically sort) the table on that column(s) to save the cost of a sort each time the column(s) is queried. Clustered indexes are also efficient for finding a specific row when the indexed value is unique. For example, the fastest way to find a particular employee using the unique employee ID column emp_id is to create a clustered index or PRIMARY KEY constraint on the emp_id column. Note PRIMARY KEY constraints create clustered indexes automatically if no clustered index already exists on the table and a nonclustered index is not specified when you create the PRIMARY KEY constraint. Alternatively, a clustered index could be created on lname, fname (last name, first name), because employee records are often grouped and queried in this way rather than by employee ID. Considerations It is important to define the clustered index key with as few columns as possible. If a large clustered index key is defined, any nonclustered indexes that are defined on the same table will be significantly larger because the nonclustered index entries contain the clustering key. The Index Tuning Wizard does not return an error when saving an SQL script to a disk with insufficient available space. For more information about how nonclustered indexes are implemented in Microsoft® SQL Server™ 2000, see Nonclustered Indexes. The Index Tuning Wizard can consume significant CPU and memory resources during analysis. It is recommended that tuning should be performed against a test version of the production server rather than the production server. Additionally, the wizard should be run on a separate computer from the computer running SQL Server. The wizard cannot be used to select or create indexes and statistics in databases on SQL Server version 6.5 or earlier. Before creating clustered indexes, understand how your data will be accessed. Consider using a clustered index for: Columns that contain a large number of distinct values. Queries that return a range of values using operators such as BETWEEN, >, >=, <, and <=. Columns that are accessed sequentially. Queries that return large result sets. Columns that are frequently accessed by queries involving join or GROUP BY clauses; typically these are foreign key columns. An index on the column(s) specified in the ORDER BY or GROUP BY clause eliminates the need for SQL Server to sort the data because the rows are already sorted. This improves query performance. OLTP-type applications where very fast single row lookup is required, typically by means of the primary key. Create a clustered index on the primary key. Clustered indexes are not a good choice for: Columns that undergo frequent changes This results in the entire row moving (because SQL Server must keep the data values of a row in physical order). This is an important consideration in high-volume transaction processing systems where data tends to be volatile. Wide keys The key values from the clustered index are used by all nonclustered indexes as lookup keys and therefore are stored in each nonclustered index leaf entry. Clustered indexes have one row in sysindexes with indid = 1. The pages in the data chain and the rows in them are ordered on the value of the clustered index key. All inserts are made at the point the key value in the inserted row fits in the ordering sequence. Microsoft® SQL Server™ 2000 indexes are organized as B-trees. Each page in an index holds a page header followed by index rows. Each index row contains a key value and a pointer to either a lower-level page or a data row. Each page in an index is called an index node. The top node of the B-tree is called the root node. The bottom layer of nodes in the index are called the leaf nodes. The pages in each level of the index are linked together in a doubly-linked list. In a clustered index, the data pages make up the leaf nodes. Any index levels between the root and the leaves are collectively known as intermediate levels. For a clustered index, sysindexes.root points to the top of the clustered index. SQL Server navigates down the index to find the row corresponding to a clustered index key. To find a range of keys, SQL Server navigates through the index to find the starting key value in the range, and then scans through the data pages using the previous or next pointers. To find the first page in the chain of data pages, SQL Server follows the leftmost pointers from the root node of the index. This illustration shows the structure of a clustered index.