Top 48 Mongodb Interview Questions You Must Prepare 14.Jun.2024

You can use the snapshot() method on a cursor to isolate the operation for a very specific case. snapshot() traverses the index on the _id field and guarantees that the query will return each document no more than once.

MongoDB preallocate data files to reserve space and avoid file system fragmentation when you setup the server.

When running a 32-bit build of MongoDB, the total storage size for the server, including data and indexes, is 2 gigabytes. For this reason, do not deploy MongoDB to production on 32-bit machines.
If you're running a 64-bit build of MongoDB, there's virtually no limit to storage size.

In replication, when MongoDB writes to a collection on the primary, MongoDB also writes to the primary's oplog, which is a special collection in the local database. Therefore, MongoDB must lock both the collection's database and the local database.

SQL databases store data in form of tables, rows, columns and records. This data is stored in a pre-defined data model which is not very much flexible for today's real-world highly growing applications. MongoDB in contrast uses a flexible structure which can be easily modified and extended.

No. MongoDB does not support default multi-document ACID tractions. However, MongoDB provides atomic operation on a single document.

Sharding is a method for storing data across multiple machines. MongoDB uses sharding to support deployments with very large data sets and high throughput operations.

When running with journaling, MongoDB stores and applies write operations in memory and in the on-disk journal before the changes are present in the data files on disk. Writes to the journal are atomic, ensuring the consistency of the on-disk journal files. With journaling enabled, MongoDB creates a journal subdirectory within the directory defined by dbPath, which is /data/db by default.

A storage engine is the part of a database that is responsible for managing how data is stored on disk. For example, one storage engine might offer better performance for read-heavy workloads, and another might support a higher-throughput for write operations.

Primary and master nodes are the nodes that can accept writes. MongoDB's replication is 'single-master:' only one node can accept write operations at a time.

Secondary and slave nodes are read-only nodes that replicate from the primary.

The explain() command can be used for this information. The possible modes are: 'queryPlanner', 'executionStats', and 'allPlExecution'.

To achieve concepts of traction and locking in MongoDB, we can use the nesting of documents, also called embedded documents. MongoDB supports atomic operations within a single document.

A Namespace is the concatenation of the database name and collection name. For e.g. school.students with school as the database and students as the collection.

Since all the fields are covered in the index itself, MongoDB can match the query condition as well as return the result fields using the same index without looking inside the documents. Since indexes are stored in RAM or sequentially located on disk, such access is a lot faster.

No. MMAPv1 does not allow configuring the cache size.

Aggregations operations process data records and return computed results. Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result. MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function, and single purpose aggregation methods and commands.

No. MongoDB does not support such relationships.

By default MongoDB does not support such primary key - foreign key relationships. However, we can achieve this concept by embedding one document inside another. Foe e.g. an address document can be embedded inside customer document.

Yes. Operations like copyDatabase(), repairDatabase(), etc. can lock more than onne databases involved.

MongoDB allows a highly flexible and scalable document structure. For e.g. one data document in MongoDB can have five columns and the other one in the same collection can have ten columns. Also, MongoDB database are faster as compared to SQL databases due to efficient indexing and storage techniques.

A NoSQL database provides a mechanism for storage and retrieval of data that is modeled in me other than the tabular relations used in relational databases (like SQL, Oracle, etc.).

Types of NoSQL databases:

  • Document Oriented
  • Key Value
  • Graph
  • Column Oriented

MongoDB uses reader-writer locks that allow concurrent readers shared access to a resource, such as a database or collection, but give exclusive access to a single write operation.

No. MongoDB can be run even on a small amount of RAM. MongoDB dynamically allocates and de-allocates RAM based on the requirements of other processes.

Currently, MonggoDB provides official driver support for C, C++, C#, Java, Node.js, Perl, PHP, Python, Ruby, Scala, Go and Erlang. MongoDB can easily be used with any of these languages. There are some other community supported drivers too but the above mentioned ones are officially provided by MongoDB.

MongoDB is a document oriented database. It stores data in the form of BSON structure based documents. These documents are stored in a collection.

Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.

By default, MongoDB created the _id collection for every collection.

GridFS is a specification for storing and retrieving files that exceed the BSON-document size limit of 16MB. Instead of storing a file in a single document, GridFS divides a file into parts, or chunks, and stores each of those chunks as a separate document.

A covered query is the one in which:

fields used in the query are part of an index used in the query, and the fields returned in the results are in the same index.

You should consider embedding documents for:

  • 'contains' relationships between entities
  • One-to-many relationships
  • Performance reasons

ObjectID is a 12-byte BSON type with:

  • 4 bytes value representing seconds
  • 3 byte machine identifier
  • 2 byte process id
  • 3 byte counter

By default configuration, MongoDB writes updates to the disk every 60 seconds. However, this is configurable with the commitIntervalMs and syncPeriodSecs options.

Yes. MongoDB supports creating text indexes to support text search inside string content. This was a new feature which can introduced in version 2.6.

  • Flexible data model in form of documents
  • Agile and highly scalable database
  • Faster than traditional databases
  • Expressive query language

Yes. The V8 JavaScript engine added in 2.4 allows multiple JavaScript operations to run at the same time.

Yes. Removing a document from database removes it from disk too.

Yes. An array field can be indexed in MongoDB. In this case, MongoDB would index each value of the array.

Although both of these databases are document oriented, MongoDB is a better choice for applications which need dynamic queries and good performance on a very big database. On the other side, CouchDB is better used for applications with occasionally changing queries and pre-defined queries.

Replication is the process of synchronizing data across multiple servers. Replication provides redundancy and increases data availability. With multiple copies of data on different database servers, replication protects a database from the loss of a single server. Replication also allows you to recover from hardware failure and service interruptions.

The database profiler collects fine grained data about MongoDB write operations, cursors, database commands on a running mongod instance. You can enable profiling on a per-database or per-instance basis.

The database profiler writes all the data it collects to the system.profile collection, which is a capped collection.

MongoDB pushes the data to disk lazily. It updates the immediately written to the journal but writing the data from journal to disk happens lazily.

If the indexes do not fit into RAM, MongoDB reads data from disk which is relatively very much slower than reading from RAM.