what is clustered and non cluster index in SQL server with example.
Key Difference between Clustered and Non-clustered Index
- A cluster index is a type of index that sorts the data rows in the table on their key values, whereas the Non-clustered index stores the data at one location and indices at another location.
- Clustered index stores data pages in the leaf nodes of the index, while the Non-clustered index method never stores data pages in the leaf nodes of the index.
- The cluster index doesn’t require additional disk space, whereas the Non-clustered index requires additional disk space.
- Cluster index offers faster data access, on the other hand, the
What is an Index?
An Index is a key built from one or more columns in the database that speeds up fetching rows from the table or view. This key helps a Database like Oracle, SQL Server, MySQL, etc. to find the row associated with key values quickly.
Two types of Indexes are:
- Clustered Index
- Non-Clustered Index
Characteristic of Clustered Index
- Default and sorted data storage
- Use just one or more than one columns for an index
- Helps you to store Data and index together
- Fragmentation
- Operations
- Clustered index scan and index seek
- Key Lookup
Characteristics of Non-clustered Indexes
- Store key values only
- Pointers to Heap/Clustered Index rows
- Allows Secondary data access
- Bridge to the data
- Operations of Index Scan and Index Seek
- You can create a nonclustered index for a table or view
- Every index row in the nonclustered index stores the nonclustered key value and a row locator
Clustered vs Non-clustered Index in SQL: Key Differences
| Parameters | Clustered | Non-clustered |
|---|---|---|
| Use for | You can sort the records and store clustered index physically in memory as per the order. | A non-clustered index helps you to creates a logical order for data rows and uses pointers for physical data files. |
| Storing method | Allows you to stores data pages in the leaf nodes of the index. | This indexing method never stores data pages in the leaf nodes of the index. |
| Size | The size of the clustered index is quite large. | The size of the non-clustered index is small compared to the clustered index. |
| Data accessing | Faster | Slower compared to the clustered index |
| Additional disk space | Not Required | Required to store the index separately |
| Type of key | By Default Primary Keys Of The Table is a Clustered Index. | It can be used with unique constraint on the table which acts as a composite key. |
| Main feature | A clustered index can improve the performance of data retrieval. | It should be created on columns which are used in joins. |
Advantages of Clustered Index
The pros/benefits of the clustered index are:
- Clustered indexes are an ideal option for range or group by with max, min, count type queries
- In this type of index, a search can go straight to a specific point in data so that you can keep reading sequentially from there.
- Clustered index method uses location mechanism to locate index entry at the start of a range.
- It is an effective method for range searches when a range of search key values is requested.
- Helps you to minimize page transfers and maximize the cache hits.
Advantages of Non-clustered index
Pros of using non-clustered index are:
- A non-clustering index helps you to retrieves data quickly from the database table.
- Helps you to avoid the overhead cost associated with the clustered index
- A table may have multiple non-clustered indexes in RDBMS. So, it can be used to create more than one index.
Disadvantages of Clustered Index
Here, are cons/drawbacks of using clustered index:
- Lots of inserts in non-sequential order
- A clustered index creates lots of constant page splits, which includes data page as well as index pages.
- Extra work for SQL for inserts, updates, and deletes.
- A clustered index takes longer time to update records when the fields in the clustered index are changed.
- The leaf nodes mostly contain data pages in the clustered index.
Disadvantages of Non-clustered index
Here, are cons/drawbacks of using non-clustered index:
- A non-clustered index helps you to stores data in a logical order but does not allow to sort data rows physically.
- Lookup process on non-clustered index becomes costly.
- Every time the clustering key is updated, a corresponding update is required on the non-clustered index as it stores the clustering key.
Suppose you have a table Employee, which contains emp_id as primary key then a clustered index which is created on a primary key will sort the Employee table as per emp_id. That was a brief introduction of What is clustered index in SQL.
On another hand, the Non-Clustered index involves one extra step which points to the physical location of the record. In this SQL Interview question, we will see some more differences between clustered and nonclustered indexes in point format.
Btw, if you are very new to SQL and don't even know what is an index, what is the real use of an index in a table, and how to create and drop an index then you should first go through these free SQL courses to start with. It's one of the best resources to learn SQL fundamentals in a quick time.
Most of the things we discuss here will make more sense if you have a basic understanding of what is n index and how they work.
What are the different types of indexing in SQL?
About the Cluster Index:-
The clustered index determines the physical order of the rows of data in the table. This
means that data is physically stored on disk.
Only one index can be created for a table because rows of data can only be sorted in one
order.
When creating an index group, the rows of data in the table are rearranged to match the
order specified by the index.
Clustered index keys are used to sort and organize data. By default, the main table is used as the join.
Because data is stored in the system in the clustered index order, retrieval of rows using a clustered index is generally faster than using a non clustered index.
Clustered indexes are especially useful for large tables that are frequently queried based
on the order of the keys in the cluster.
If the table does not have an index, it is called a heap and the data is stored out of order.
The non clustered index is an independent model of the data row containing a copy
of the index column and a pointer to the actual data row.
Multiple exclusion indexes can be created in a single table. Not every measure includes its own model.
Non clustered indexes are useful for improving the performance of queries that involve
searching, filtering, and indexing on rows that are not part of a cluster index.
In SQL Server, you can have multiple index exclusions on a table. The number of non-container indexes that can be created on a table is determined by the maximum limit set by the database engine.
The maximum number of indexes allowed for a table in SQL Server is 999. However, it's
important to note that adding more indexes to tables can negatively affect performance
because each index incurs a storage overhead to manage during data changes. such as
additions, updates and deletions. Therefore, it is important to carefully consider the need for additional indexes and ensure they are designed to optimize most queries on the table.
- Clustered indexes are generally more efficient for retrieving large ranges of data in the order defined by the index key.
- They eliminate the need for sorting when querying data in the order of the clustered index key.
- They can be beneficial for tables frequently accessed sequentially or when there is a need for frequent range queries.
- A table can have only one clustered index, and it determines the physical order of data rows. Therefore, choosing the right clustered index key is crucial.
- When a clustered index is created or modified, it may cause a significant amount of data movement and can be time-consuming.
- Non-Clustered Index:
- Benefits:
- Non-clustered indexes are useful for improving the performance of specific queries involving search, filter, and sort operations on columns that are not part of the clustered index.
- They allow for efficient retrieval of individual rows based on the indexed columns.
- Multiple non-clustered indexes can be created on a table, providing flexibility to optimize different query patterns.
- Non-clustered indexes require additional storage space to store the index structures.
- Insert, update, and delete operations on the indexed columns may have a slight performance overhead as the indexes need to be maintained alongside the data.
- Clustered Index: A clustered index determines the physical order of data rows in a table. In other words, it defines the way data is physically stored on disk. Each table can have only one clustered index. When a table has a clustered index, the data rows are sorted and stored based on the values in the indexed column(s).
Non-Clustered Index: A non-clustered index is a separate structure from the actual data rows and does not dictate the physical order of the data. It has its own storage structure, containing a copy of the indexed column(s) along with a reference to the corresponding data row. A table can have multiple non-clustered indexes.
Now, let's discuss the performance aspects:
- Clustered Index: Since the data rows in a table with a clustered index are physically ordered based on the index key, retrieving data using the clustered index can be faster when the query requires accessing a range of data or retrieving all the rows in the table. However, if the query needs to search based on a different column or involves complex joins and filtering, the clustered index might not be as efficient, as it dictates the physical order of the data
Non-Clustered Index: Non-clustered indexes are useful for efficient searching and retrieval based on columns other than the clustered index key. They provide quick access to specific rows based on the indexed column(s). Non-clustered indexes are particularly helpful when executing queries involving filtering, sorting, and joining operations on columns other than the clustered index. However, accessing the actual data rows might require an additional lookup step, which can introduce some overhead compared to the clustered index.
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