Question 1

Which of these statements is/are true?

 Answer:
  • You can index multiple array fields in a single document with a single compound index - False 
    Multikey indexes allow us to index on array fields, but they do not support indexes on multiple array fields on single documents.
  • Covered queries can sometimes still require some of your documents to be examined - False
    A query is covered if and only if it can be satisfied using the keys of the index.
  • Write concern has no impact on write latency - False
    Different write concerns can certainly impact your write latency. Write concerns that only need acknowledgment from a primary are generally faster than ones that need acknowledgment from a majority of replica set members.
  • Creating an ascending index on a monotonically increasing value creates index keys on the right-hand side of the index tree - True
  • A collection scan has a logarithmic search time - False
    No, collection scans have a linear search time.


Comments

Post a Comment

Popular posts from this blog

M201 MongoDB Performance - Labs & Final Exam Q&A

M201 MongoDB Performance Chapter-1 Introduction to MongoDB Performance Lab 1.1: Install Course Dependencies Lab 1.2: Install MongoDB Compass Chapter – 2 MongoDB Indexes Lab 2.1: Using Indexes to Sort Lab 2.2: Optimizing Compound Indexes Chapter – 3 Index Operations Lab 3.1: Explain Output Chapter 4: CURD Optimization Lab 4.1 – Equality, Sort, Range Chapter 5: Performance on Clusters Final Exam Question 1 Question 2 Question 3 Question 4 Question 5 Question 6 Question 7
Read more

Lab 2.1

Image
In this lab you're going to determine which queries are able to successfully use a given index for both filtering and sorting. Given the following index: {"first_name": 1, "address.state": -1, "address.city": -1, "ssn": 1} Which of the following queries are able to use it for both filtering and sorting? Check all that apply: Answer: db.people.find({ "first_name": { $gt: "J" } }).sort({ "address.city": -1 }) - No - This query doesn't use equality on the index prefix. When using an index for filtering and sorting the query must include equality conditions on all the prefix keys that precede the sort keys. Moreover, on the sort predicate it skipped the next key in the prefix "address.state". db.people.find({ "first_name": "Jessica" }).sort({ "address.state": 1, "address.city": 1 }) - Yes . This query matches with equality on the query predicate wit
Read more

Question 7

Image
Given the following indexes: { categories: 1, price: 1 } { in_stock: 1, price: 1, name: 1 } The following documents: { price: 2.99, name: "Soap", in_stock: true, categories: ['Beauty', 'Personal Care'] } { price: 7.99, name: "Knife", in_stock: false, categories: ['Outdoors'] } And the following queries: db.products.find({ in_stock: true, price: { $gt: 1, $lt: 5 }  }).sort({  name: 1 }) db.products.find({ in_stock: true }) db.products.find({ categories: 'Beauty'  }).sort({  price: 1 }) Whic h of  following is/are true? Answer: Index #1 would provide a sort to query #3. - True Index #2 properly uses the equality, sort, range rule for query #1. - False - If we were to build an index for query #1 using the equality, sort, range rule, then the index would be: { in_stock: 1, name: 1, price: 1 }. There would be a total of 4 index keys created across all of these documents and indexes. - False - As there would be 5 to
Read more