50 Important MongoDB Interview Questions and Answers(2021)
Introduction
MongoDB is utilized by a variety of businesses in a variety of domains. According to a study, it is used by 26,929 companies. Companies that use MongoDB are mainly in the computer software sector in the United States. Companies of 10-50 workers and of revenue ranging from $1 million to $10 million benefit highly from MongoDB. If you are preparing for a job interview that needs MongoDB expertise, this article would be your one-stop guide for MongoDB interview questions. You will read about various concepts of sharding, slicing and much more.
So, let’s have a look at the 50 top MongoDB interview questions and answers.
List of MongoDB interview questions
- What do you know about Mongo shell?
Mongo shell is a JavaScript interface to MongoDB that allows you to query and upgrade data. It is collaborative and can be used for administrative tasks.
- What is a storage engine? What are the different types of storage engines available in MongoDB?
The storage engine is the database part in charge of handling how data is processed, both in memory and on disk. MongoDB accepts many storage engines since various engines are best suited to different workloads.
- The default storage engine is the WiredTiger storage engine. It is suitable for the majority of workloads and is recommended for modern implementations. WiredTiger includes, among other things, a document-level concurrency model, checkpointing and compression.
- MongoDB Enterprise has an in-memory storage engine. It keeps records in memory rather than on disks for more predictable storage latencies.
- MMAPv1 storage engine is discontinued as of MongoDB v4.0, but it was the default storage engine for MongoDB versions 3.0 and earlier.
- How would you use MapReduce for grouping over 10000 unique keys?
By using version 2.2 of MapReduce for grouping. The returned array from the db.collection.group() method will include up to 20,000 elements, implying up to 20,000 distinct groupings. Previous versions of MapReduce have a total of 10,000 elements for the group by operations of more than 20,000 distinct groupings.
- What specifically is a collection in MongoDB?
A group of documents is referred to as a collection. If a document is the MongoDB analog of a row in a relational database, then a collection is the MongoDB analog of a table.
Dynamic schemas exist in collections. This indicates that the documents included inside a single collection may be of any shape. It’s worth noting that the previous documents’ values are not just of different types (string and integer), but they often have completely different keys. Any document can be added to any collection in MongoDB.
- What are 32-bit nuances?
With journaling, there is an additional memory-mapped file activity. This would also restrict the restricted database size of 32-bit builds. Journaling is now disabled by default on 32-bit computers.
- Give a comparison between MongoDB and Cassandra.
| Criteria | MongoDB | Cassandra |
| Data model | Document | Bigtable |
| Database scalability | Read | Write |
| Querying of data | Multi-indexed | Using key or scan |
- What exactly do you mean by NoSQL databases? Is MongoDB a NoSQL database? Please elaborate.
The internet is now filled with huge data, users, complexities, etcetera, and it is also getting more nuanced by the day. NoSQL is the solution to all of these issues. It is not a standard database management system, nor is it a relational database management system (RDBMS). NoSQL is an abbreviation for “Not Only SQL”. NoSQL is a database that can manage and filter all types of unstructured, jumbled and complicated data. It’s also a different way of looking at the database. MongoDB is a NoSQL (no-SQL) database.
*MongoDB NoSQL is one of the most frequently asked MongoDB interview questions.
- What are the advantages and disadvantages of normalizing data in a MongoDB database?
Documents are updated quickly for normalized data and slowly for denormalized data, much as in standard RDBMSes. Reading documents, on the other hand, is faster in denormalized data and slower in normalized data. Denormalized data is more difficult to maintain and takes up more room.
It should be noted that in MongoDB, denormalized data is more commonly anticipated. This is because RDBMSes have built-in support for normalization and enable data to be handled as a separate issue, while NoSQL DBMSes like MongoDB does not.
Instead, normalization necessitates that client applications carefully protect their own integrity. To help with this, audits may be performed to ensure the app data conforms to anticipated patterns of referential integrity.
- What are NoSQL databases? What are the various kinds of NoSQL databases?
A NoSQL database is a method for storing and retrieving data that is not modeled through the tabular relations found in relational databases (like SQL, Oracle, etc.).
NoSQL databases types include:
- Document-oriented
- Key-value
- Graph
- Column-oriented
*You should be prepared to be asked multiple NoSQL interview questions. So prepare accordingly.
- Define what is “Namespace” in MongoDB?
In the collection, MongoDB stores BSON objects. A namespace is the concatenation of the collection name and the database name.
- How is data stored in MongoDB?
Since MongoDB is document-based, data is stored in BSON or Binary JavaScript Object Notation, which is the binary-encoded format of JSON.
- How can you query real-time MongoDB data?
Using the utilities mentioned can help handle live MongoDB data.
- MongoHub has been migrated to a native Mac version.
- This comes in handy with tree and document views.
- Genghisapp – this is a web-based GUI that is clean, light-weight, easy to use, has keyboard shortcuts and performs fantastically well. GridFS is also supported.
- Will there be journal replay programs in the event of an unfinished entry (or a failure in the middle of one)?
Each journal (group) entry is reliable and it will not be replayed during recovery until it is completed.
- What distinguishes MongoDB as the best?
MongoDB is regarded as the strongest NoSQL database due to the following characteristics:
- Document-oriented (DO)
- High performance (HP)
- High availability (HA)
- Scalability is easy
- Rich query language
- What are the various languages that MongoDB supports?
MongoDB officially supports the following languages: C, C++, C#, Java, Node.js, Perl, PHP, Python, Ruby, Scala, Go and Erlang. MongoDB can be used for any of the languages mentioned above. There are several other community-supported drivers, but the ones mentioned above are given by MongoDB.
Introduction
The index is named as a design in SQL server stored or maintained wilt in-memory structure or on disk related with a table or views, which is utilized principally to recognize a specific set or a row Table or Views. Indexes in SQL are the individual lookup tables, which are utilized by the data set internet searcher to accelerate the general information recovery.
The use of the index in SQL is to rapidly discover the data in a data set table without looking through each row of it. In SQL Index, it is basic to keep up more extra storage to make a copy duplicate of the data set. Tables in SQL server are contained inside database item holders that are called Schemas. The schema likewise fills in as a security limit, where you can restrict data set client authorizations to be on a particular schema level as it were. To know what are the different types of Indexes in SQL Server, then read this article to explore them and have a better understanding of them.
Different Types of Indexes in SQL Server
There are various types of indexes in SQL server:
1. Clustered Index
Clustered Index store and sort rows of data in a view or table depending on their central values. There may be an instance of having just one clustered index in each table, as it can empower the client to store data in a solitary request. Clustered index store data in an arranged way, and in this way, at whatever point data is contained in the table in an arranged manner implies it is orchestrated with a clustered index.
At the point when a table contains a clustering in SQL server, it is named a clustered table. A clustered index is liked to utilize when adjustment of gigantic information is needed in any data set. If the data put away in a table or data set are not organized in descending or ascending request, at that point, the data table is named as a heap.
2. Non-Clustered Index
It represents a structure, which is isolated from data rows. This types of indexes in SQL server covers the non-clustered key values, and each worth pair has a pointer to the data row that comprises vital significance.
In the non-clustered index, the client can undoubtedly add non-key to the leaf level, as it sidesteps the current index key cut-off points and performs completely covered recorded questions. A non-clustered index is made to improve the general exhibition of much of the time posed inquiries, which are not covered by grouped things.
Clustered vs. Non-clustered index in SQL server is that the non-clustered index stores the data at one area and indices at another area, while the clustered index is a kind of index that sorts the data rows in the table on their key values.
3. Column store Index
A column store index is one of the types of indexes in SQL Server that has a standard type of index with regards to putting away and questioning enormous data warehousing truth tables. This is an index of SQL, which was intended for development in the presentation of inquiry in the event of jobs with huge measures of data.
The column-store index empowers putting away information inside little impressions, which helps in speeding up. The use of this index takes into account the client to get IO with multiple times higher inquiry execution when contrasted with conventional column arranged capacity. For examination, the Columnstore Index gives a significant degree to have a preferable exhibition over other records in SQL. Column store index esteems from a similar area have comparative qualities, which expands the general pace of information compressions.
4. Filtered Index
A filtered index is one of the types of indexes in SQL server that is made when a column has just a few applicable numbers for questions on the subset of values. If, when a table comprises heterogeneous data rows, a separated list is made in SQL for at least one sorts of data.
5. Hash Index
Hash Index is one of the types of indexes in SQL server that slots containing a pointer or an array of N buckets and a row on each slot or bucket. It utilizes the Hash function F (K, N), where N is several buckets and K is critical. The capacity delineates the key relating to the bucket of the hash index. Every bucket of the Hash Index comprises eight bytes, which is utilized to stock the memory address of the connected rundown of basic sections.
6. Unique Index
The unique index in the SQL server confirms and guarantees that the index key doesn’t contain any copy esteems and along these lines, empowers the clients to examine that each row in the table is exceptional in either way.
The unique index in SQL extraordinarily utilized when the client needs to have an extraordinary trait of every information. It permits people to guarantee the data respectability of each characterized section of the table in the data set. This index likewise gives extra data about the data table, which is useful to question enhancer.
Types of Pages in SQL server
- Data Pages
- Bulk Changed Map
- Text/Image Pages
- Page Free Space
- Index Allocation Map
- Secondary Global Allocation Map
- Differential Changed Map
- Global Allocation Map
Types of the Database in SQL server
- tempdb
- msdb
- Master
- Model
Conclusion
To create an index in the SQL statement is utilized to make files in tables. Indexes are utilized to recover information from the data set more rapidly than something else. The clients can’t see the lists, they are simply used to accelerate queries/searches.
An Index is a key worked from at least one column in the information base that speeds up getting rows from the view or table. This key aids a Database like MySQL, SQL Server, Oracle, and so on to discover the row related to key qualities rapidly.
An index stores the total information in the table, which is coordinated coherently with rows and columns, and truly kept up and put away in line shrewd data known as row store and if the records are stored away in segment insightful data, known as Columnstore.
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*This is one of the most frequently asked MongoDB interview questions.
- What are the similarities and differences between sharding and replication in MongoDB?
Both sharding and replication require the use of several instances to host the database. Replicas are MongoDB instances that contain identical data, hence the name. To maximize redundancy and availability, we use replicas. In contrast, for sharding, each shard instance has data that is distinct from its neighbors. For horizontal scaling, we use sharding.
*Replication interview questions are quite commonly asked in interviews.
- On a high level, compare SQL databases and MongoDB.
SQL databases store data in the form of tables, rows, columns and documents. This data is contained in a pre-defined data format, which is not quite scalable for today’s rapidly increasing real-world applications. MongoDB, on the other hand, employs a modular framework that can be quickly changed and expanded.
- How do you see the Mongos connection?
To see the connection used by MongoDB, use DB admin command (“connPoolStats”);
- What are MongoDB’s data models?
The structure of documents influences data modelling. Related data in MongoDB may be embedded in a single document structure (embedded data model). Through references from one document to another, the relationship between data is stored. It is called the normalized data model.
- How do you use MongoDB to update a certain key/value of an array field?
Assume we have a list of content that includes blogs, news and so on. These articles have another array named the author, which includes all of the author’s material.
db.content.update (‘authors.abc’:’xyz’,$set:‘authors.$.address’:’Address That I wanted’,false,true); This correctly changes all of the records.
- What is the role of a profiler in MongoDB?
MongoDB provides a database profiler that displays the performance characteristics of each database process. Using this profiler, you may identify queries (and write operations) that are taking longer than they should and use this information to determine when an index is needed.
*This is one of the most frequently asked MongoDB interview questions.
- What exactly is a replica set?
A replica set is a collection of mongo instances that all host the same data set. One node in a replica set is primary and another is secondary. All data is replicated from the main to the secondary node.
- Does MongoDB write to disk automatically or slowly?
MongoDB writes data to disk in a haphazard fashion. It changes the data that is automatically written to the server, but it writes the data from the journal to disk slowly.
- What are the main distinctions between BSON documents in MongoDB and JSON documents in general?
JSON (JavaScript Object Notation), like XML, is a human-readable data exchange standard. JSON has been the most commonly adopted data exchange standard on the web. JSON accepts booleans, numbers, sequences and arrays as data types. BSON, on the other hand, is the binary encoding used by MongoDB to store its documents. It is equivalent to JSON, but it expands JSON to accept additional data types, such as Date. Unlike JSON records, BSON documents are ordered. BSON usually uses less room than JSON and traverses easier. Since it is binary, BSON is, therefore, faster to encrypt and decode.
- How does MongoDB handle transactions or locking?
MongoDB does not use traditional locking with reduction since its presentation is intended to be light, quick and understandable. It can be compared to the MySQL MyISAM auto entrust sculpt. Performance is improved with the simplest business maintenance, particularly in a structure with several servers.
- Is it possible to establish primary key – foreign key relationships in MongoDB?
By embedding one document within another, we may achieve a primary key-foreign key relationship. For instance, an address document may be inserted inside a customer document.
- MongoDB is referred to as a schema-less database. Is this true? How can you make a schema in MongoDB?
Since JSON is a schema-free data system, it will be more accurate to assume that MongoDB has a dynamically typed schema. Create and insert a text to begin creating a schema. When a document is entered into the database, a corresponding collection is generated.
- In MongoDB, how do you use the primary key?
In MongoDB, the _id field is reserved for the primary key, and it has a unique value. If you don’t specify anything for _id, it will be filled with “MongoDB Id Object.” However, you can enter some unique information in that field.
- Is an object attribute deleted from the store as it is removed?
Yes, you can erase the attribute and then re-save() the object.
*Basic MongoDB interview questions like these are quite frequently asked to test the basic knowledge of the candidate.
- When and to what degree does data become multi-slice?
MongoDB scrap stands on a collection. As a result, an album containing all substances is stored in the form of a lump or mass. Where an extra time period is available there can be more than a few slice data accomplishment options, so when there is more than one chunk, data is extended to a large number of slices and can be extended to 64 MB.
- Is it essential for MongoDB to have a ton of RAM?
No, it does not. MongoDB does not need a ton of RAM to operate. It can operate on very little RAM because it dynamically allocates and deallocates RAM based on the needs of the processes.
- “When you add more slaves to a replica set, both writes and reads become faster.” Is this claim correct or incorrect? Why is this so?
False. All write operations are only performed on the master. Read operations, on the other hand, may be performed on any instance — slave or master. As more slaves are added to a replica set, only reads get faster.
- What is the replication mechanism in MongoDB?
The process of synchronizing data through several servers is known as replication. With several copies of data on various database servers, it offers continuity and increases data efficiency. Replication protects the database from the loss of a single server.
- What do you know about MongoDB indexes?
In MongoDB, indexes aid in the effective execution of queries. Without indexes, MongoDB must conduct a collection scan, which involves scanning each document in a collection to find those that fit the query statement. If a query has an appropriate index, MongoDB may use the index to restrict the number of documents it must inspect.
- In MongoDB, how can CRUD operations be performed?
C – stands for create – db.collection.insert();
R – stands for read – db.collection.find();
U – stands for update – db.collection.update();
D – stands for delete – db.collection.remove({“fieldname” : ”value”});
- Describe oplog.
The operational log (oplog) is a kind of capped collection that maintains a running record of all operations that change the data in your databases. It first performs database operations on the primary, after which it logs these operations in the primary’s log. The secondary members then copy and execute these operations in an asynchronous method.
- Are null values permitted?
Yes, it’s only for the members of an object. Since a null is not an object, it cannot be attached to the database collection. However, {} can be added.
- Compare MongoDB with Couchbase and CouchbaseDB.
While MongoDB, Couchbase and Couchbase DB have several similarities, they vary in terms of model execution requirements, crossing points, storage, duplications and so on.
- What language is MongoDB written in?
MongoDB is written and coded in C++.
- In MongoDB, is it possible to construct an index on an array field? What occurs if this is the case?
Yes. In MongoDB, an array field may be indexed. In this scenario, MongoDB will index each array value.
- What factors should be considered while constructing a schema in MongoDB?
The following points must be considered:
- Create the schema in accordance with the needs of the users.
- If you use several objects together, combine them into a single document. Separate them if necessary.
- Do joins while writing, not while reading.
- Optimize the schema with the most common use cases.
- In the schema, perform complex aggregation.
- In MongoDB, how are constraints managed?
Starting with MongoDB 3.2, you can add a document validator to collections. Unique indexes can also be formed using db.collection. createIndex(“key”: 1, );
- What is the structure of ObjectId?
It is made up of the following components:
- Client process ID
- Timestamp
- Client machine ID
- Byte incremented counter
- Does an update sync to the disk immediately?
No, it does not. By default, disk writes are lazy. A write cannot reach the disk for many seconds. For example, if the database receives a thousand increments to an object in one second, the object can only be flushed to disk once (it should be noted that fsync options are accessible both at the command line and via getLastError_old).
- How can we move an older file into the moveChunk directory?
When the functions are completed, the old files are converted to backup files and relocated to the moveChunk directory during the slice balancing process.
- What is the procedure for configuring the cache size in MongoDB?
The cache in MongoDB is not configurable. Actually, MongoDB uses all of the system’s free space automatically through memory-mapped files.
- What is the significance of a covered query?
Since the index contains all of the fields, MongoDB will fit the question condition and return the result fields without having to search into the documents. Since indexes are contained in RAM or sequentially on disk, such access is much quicker.
- What is the command syntax for determining whether or not you are on the master server? And how many masters can MongoDB support?
Db.isMaster() command syntax will inform you whether you are on the master server or not. MongoDB only supports one master server, while CouchDB supports several masters.
- What exactly is journaling, and how does it function?
MongoDB maintains data integrity by creating an on-disk journal for each write. In the event of a server failure, the log will be used to detect writes that were not written to the disk or data files.
- What is the difference between a secondary and a slave?
Conclusion
Follow the top simple and advanced MongoDB interview questions to become an indispensable MongoDB developer. We’ve answered the most frequently asked MongoDB interview questions. With these top MongoDB interview queries, you can understand the detailed framework of MongoDB as well as the various applications of MongoDB. These can qualify you to work as a MEAN stack developer, backend engineer, front-end developer and in a variety of other positions. Learning MongoDB would undoubtedly help your career because the industry demand for MongoDB is growing at a rapid rate.
If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional.
