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The topics covered in the MongoDB C100DBA Exam include MongoDB architecture, data modeling, indexing, replication, sharding, security, backup and recovery, and performance tuning. C100DBA exam is designed to test the candidate's practical skills in administering MongoDB databases, including the ability to troubleshoot common issues and optimize database performance.

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MongoDB C100DBA Certification is a highly valuable certification for professionals looking to demonstrate their expertise in MongoDB database administration. With its focus on the latest version of MongoDB, the certification is an excellent way to demonstrate proficiency in this highly sought-after database technology. By preparing for and obtaining this certification, professionals can advance their careers and increase their earning potential.

MongoDB Certified DBA Associate Exam (Based on MongoDB 4.4) Sample Questions (Q155-Q160):

NEW QUESTION # 155
Which of the following commands will return all the posts with number of likes greater than 100 and less than 200, both inclusive?

A. db.posts.find({ likes : { $gte : 100, $lt : 200 } } );
B. db.posts.find({ likes : { $gte : 100 , $lte : 200 } } );
C. db.posts.find({ likes : { $gt : 100, $lt : 200 > > );
D. db.posts.find({ likes : { $gt : 100 , $lte : 200 } } );

Answer: B

NEW QUESTION # 156
Below is a sample document of "orders" collection

A. $sort

Answer: A

NEW QUESTION # 157
If you have created a compound index on (A,B, C) which of the following access pattern will not be able to utilize the index?

A. A
B. B, C
C. A, B, C
D. A, B

Answer: B

NEW QUESTION # 158
In order to ensure that you can maintain high availability in the face of server failure, you should implement which of the following?

A. Sharding
B. Properly defined user roles
C. Put indexes on all of your documents
D. Replication
E. The proper storage engine

Answer: D

NEW QUESTION # 159
Consider a clothing collection that contains these documents:
{ " _id " : 1, " item " : " sweater " , " sizes " : [ " XS " , " S " ] }
{ " _id " : 2, " item " : " t-shirt " , " sizes " : [ " S " , " M " , " XL " ] }
{ " _id " : 3, " item " : " vest " , " sizes " : [ " M " , " L " , " XL " , " XXL " ] } What does the following query return?
db.clothing.find({ " sizes " : " M " })

A. Only document _id: 3.
B. All three documents.
C. Only document _id: 2.
D. Documents _id: 2 and _id: 3.

Answer: D

Explanation:
MongoDB supports direct equality matching against elements contained in an array. When the predicate is { sizes: " M " } and sizes is an array field, a document matches when at least one element of the array equals the scalar value " M " . Document 1 contains only " XS " and " S " , so it does not match. Document 2 contains " M " in [ ' S ' , ' M ' , ' XL ' ], and document 3 contains " M " in [ ' M ' , ' L ' , ' XL ' , ' XXL ' ]; both therefore match. No $elemMatch expression is required for this simple scalar membership test. $elemMatch becomes important when multiple conditions must be satisfied by the same array element, particularly for arrays of embedded documents or compound conditions. This array equality behavior is a core part of MongoDB ' s document query model and allows concise filtering of array-valued fields. The correct result is consequently the t-shirt and vest documents, which corresponds to option D. This same matching behavior applies consistently whenever a scalar predicate targets values stored inside a BSON array field.
Study Guide reference/topic:MongoDB Architecture and Core Operations - querying array fields and equality predicates.

NEW QUESTION # 160
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