Mongodb Creating And Dropping Indexes Complete Guide
Understanding the Core Concepts of MongoDB Creating and Dropping Indexes
MongoDB Creating and Dropping Indexes
Creating Indexes in MongoDB
1. Collection Method:
To create an index on a single field or multiple fields, you can use the createIndex() method on a collection. This method accepts an index specification document that describes the index key and field to be indexed.
Syntax:
db.collection.createIndex(keys, options)
- keys: The index specification document specifies the field(s) and sorting order (1 for ascending, -1 for descending).
- options: An optional document containing index creation options.
Example:
Creating a single field index on the username field in ascending order:
db.users.createIndex({ username: 1 })
Creating a compound index on the username field (ascending) and age field (descending):
db.users.createIndex({ username: 1, age: -1 })
2. Create Unique Indexes:
To ensure that no two documents in a collection have the same value for a particular field or set of fields, you can create a unique index. MongoDB provides the unique option in the options document to achieve this.
Example:
Creating a unique index on the email field:
db.users.createIndex({ email: 1 }, { unique: true })
3. Create a Sparse Index:
A sparse index is a special type of index that includes entries only for documents that have the indexed field. Sparse indexes can reduce the space required for storing an index and improve performance for queries that filter on indexed fields.
Example:
Creating a sparse index on the profile field:
db.users.createIndex({ profile: 1 }, { sparse: true })
Dropping Indexes in MongoDB
When an index is no longer needed, it can be dropped to free up storage space and improve write performance. MongoDB provides the dropIndex() method for this purpose.
Syntax:
db.collection.dropIndex(indexName)
- indexName: The name of the index to be dropped.
Example:
Dropping an index named username_1:
db.users.dropIndex('username_1')
1. Dropping All Indexes on a Collection:
To drop all indexes other than the default _id index on a collection, you can use the dropIndexes() method.
Syntax:
db.collection.dropIndexes()
Example:
Dropping all indexes on the users collection:
db.users.dropIndexes()
Important Information
Performance Impact: Creating or dropping indexes can have performance implications. It is advisable to perform these operations during low-traffic times.
Index Size: MongoDB requires extra storage for indexes. Consider disk space when designing indexes.
Compound Indexes: Compound indexes can significantly improve query performance, but they consume more storage and can slow down write operations.
Default Index: The
_idfield is indexed by default, and this index cannot be dropped.Background Indexing: To avoid blocking writes, MongoDB supports background indexing through the
backgroundoption.Example: Creating a background index on the
usernamefield:
Online Code run
Step-by-Step Guide: How to Implement MongoDB Creating and Dropping Indexes
Prerequisites
- MongoDB installed and running.
- Access to the MongoDB shell (
mongo) or a MongoDB client like Robo 3T. - Familiarity with basic MongoDB commands.
Example Setup
Let's assume we have a database named library and a collection named books. We'll start by creating some sample documents in the books collection.
// Connect to MongoDB shell or use your MongoDB client
mongo
// Use the library database or create if it does not exist
use library
// Insert sample documents into the books collection
db.books.insertMany([
{ title: "1984", author: "George Orwell", isbn: "0452284236", publishedYear: 1949 },
{ title: "To Kill a Mockingbird", author: "Harper Lee", isbn: "0061120081", publishedYear: 1960 },
{ title: "Brave New World", author: "Aldous Huxley", isbn: "0060935464", publishedYear: 1932 },
{ title: "The Catcher in the Rye", author: "J.D. Salinger", isbn: "0316769487", publishedYear: 1951 }
]);
Creating Indexes
Step 1: Understanding Index Basics
Indexes in MongoDB are special data structures that improve the efficiency of data retrieval operations on a collection. Indexes are created on one or more fields in a collection.
Step 2: Creating a Single Field Index
Let's create an index on the author field of the books collection to improve query performance on that field.
// Create a single field index on the 'author' field
db.books.createIndex({ author: 1 });
Here, 1 indicates ascending order. You can use -1 for descending order if needed.
Step 3: Creating a Compound Index
If you frequently query the books collection using a combination of author and publishedYear, consider creating a compound index.
// Create a compound index on the 'author' and 'publishedYear' fields
db.books.createIndex({ author: 1, publishedYear: 1 });
Step 4: Viewing Indexes
You can view all the indexes on the books collection to confirm they were created successfully.
// List all indexes on the 'books' collection
db.books.getIndexes();
Dropping Indexes
Step 1: Dropping a Single Field Index
To drop the index on the author field, you can use the dropIndex method.
// Drop the index on the 'author' field
db.books.dropIndex({ author: 1 });
Step 2: Dropping a Compound Index
Similarly, to drop the compound index on the author and publishedYear fields:
// Drop the compound index on the 'author' and 'publishedYear' fields
db.books.dropIndex({ author: 1, publishedYear: 1 });
Conclusion
Creating and dropping indexes in MongoDB is straightforward with the createIndex and dropIndex methods, respectively. Indexes help speed up query operations, but they also consume storage space, so they should be used judiciously.
Additional Tips
- Always monitor the performance of your queries and adjust indexes accordingly.
- Indexes can be unique (ensures no two documents have the same value).
- Use the
explainmethod to analyze how queries use indexes.
// Example of using explain to analyze the query execution plan
db.books.find({ author: "George Orwell" }).explain("executionStats");
Top 10 Interview Questions & Answers on MongoDB Creating and Dropping Indexes
1. What is an index in MongoDB?
Answer: An index in MongoDB is a data structure that improves the efficiency of database operations like querying, sorting, and joining by storing a small portion of the collection's data set in an easy-to-traverse form. Just as an index in a book helps you locate information more quickly than searching each page manually, a MongoDB index helps the database find documents faster.
2. How do you create a single-field index?
Answer: To create a single-field index on the fieldName field in the collectionName, you can use the following command in the MongoDB shell or any MongoDB driver:
db.collectionName.createIndex({ fieldName: 1 })
In this example, 1 denotes ascending order; if you want to sort in descending order, use -1.
3. How do you create a compound index?
Answer: A compound index consists of multiple fields. Here's how to create one:
db.collectionName.createIndex({ field1: 1, field2: -1 })
This will first sort the documents in ascending order based on field1 and then in descending order based on field2 when field1 values are the same.
4. Can I create multiple indexes at once?
Answer: While createIndex() creates one index per call, you can create multiple indexes on a collection with a single call using the createIndexes() method:
db.collectionName.createIndexes([
{ key: { field1: 1 }, name: "indexField1" },
{ key: { field2: -1 }, name: "indexField2" }
])
5. When should you drop an index?
Answer: You should drop an index when:
- It's not being used.
- You are performing frequent writes and the index slows down the insert/update/delete operations.
- Storage space is a concern.
- The index was created on a frequently changing attribute that no longer makes sense to have indexed.
6. How do you check the list of indexes on a collection?
Answer: Use the getIndexes() method:
db.collectionName.getIndexes()
This command returns an array of documents, where each document represents an index on the collection.
7. How do you drop a specific index from a collection?
Answer: Specify either the index name or the fields it covers to the dropIndex() method:
// By index name
db.collectionName.dropIndex("indexName")
// By fields covered
db.collectionName.dropIndex({ fieldName: 1 })
8. Are there any special considerations for indexing large collections?
Answer: Yes, indexing large collections requires careful planning:
- Disk Usage: Indexes consume additional disk space; ensure your storage can handle them.
- Index Build Time: Index creation can take considerable time on large datasets.
- Write Performance: Indexes slow down write operations because MongoDB needs to update them whenever a document is inserted, updated, or deleted.
- Index Size Growth: Regularly monitor the growth and usefulness of the indexes.
9. How do you ensure that a unique index doesn't allow duplicate entries?
Answer: Add the {unique: true} option while creating the index:
db.collectionName.createIndex(
{fieldName: 1},
{unique: true}
)
This instructs MongoDB to ensure all indexed field values are unique.
10. How does MongoDB handle the deletion of a collection or database, and its associated indexes?
Answer: When you drop a collection using drop(), MongoDB automatically removes all indexes associated with that collection. Similarly, dropping a database results in the deletion of all collections within it, including all their indexes. For instance:
// Drop Collection
db.collectionName.drop()
// Drop Database
db.dropDatabase()
This ensures data integrity and prevents unnecessary storage use after the collections or databases are no longer needed.
Additional Tips:
- Partial Indexes: These can be useful for indexing only a subset of documents in a collection, which can lead to faster writes if not all documents need to be indexed by certain criteria.
- Text Indexes: Use these if you perform text searches on fields; they facilitate fast full-text searches over string contents.
- TTL (Time-To-Live) Indexes: Ideal for documents that expire after a certain period, such as session data or temporary logs. They help in removing old/expired documents automatically, keeping the dataset lean.
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