M101js Homework 4.1

Learn everything you need to know to get started building a MongoDB-based app. This course will go over basic installation, JSON, schema design, querying, insertion of data, indexing and working with the C# driver. In the course, you will build a blogging platform, backed by MongoDB.

Details

  • Duration: 7 weeks
  • Each week we release new video lectures and a new assignment.
  • Your final grade for the course will be comprised of weekly assignments which count for half of your grade and a final exam/project which counts for the other half of your grade.
  • You will receive a certificate of completion at the end of the course if you achieve a 65% or above on graded material.

Objective

After completing this course, you should have a good understanding as to how applications are built on top of MongoDB using the .NET framework. This course should also prepare you to take the C100DEV: MongoDB Certified Developer, Associate Level exam. Register for next exam session to become a MongoDB Certified Professional.

Prerequisites

To take this course you should be familiar with the .NET framework. Knowledge of relational databases is not required.

 [Solution] Week 4 :Performance : M101P: MongoDB for Developers

Homework 4.1 : 

Suppose you have a collection with the following indexes:

> db.products.getIndexes() [ { "v" : 1, "key" : { "_id" : 1 }, "ns" : "store.products", "name" : "_id_" }, { "v" : 1, "key" : { "sku" : 1 }, "unique" : true, "ns" : "store.products", "name" : "sku_1" }, { "v" : 1, "key" : { "price" : -1 }, "ns" : "store.products", "name" : "price_-1" }, { "v" : 1, "key" : { "description" : 1 }, "ns" : "store.products", "name" : "description_1" }, { "v" : 1, "key" : { "category" : 1, "brand" : 1 }, "ns" : "store.products", "name" : "category_1_brand_1" }, { "v" : 1, "key" : { "reviews.author" : 1 }, "ns" : "store.products", "name" : "reviews.author_1" } ]

Which of the following queries can utilize at least one index to find all matching documents, or to sort? Check all that apply.

Note: the text for some answers may wrap; you can ignore the wrapping.



Homework 4.2 : 

Suppose you have a collection called tweets whose documents contain information about the created_at time of the tweet and the user's followers_count at the time they issued the tweet. What can you infer from the following explain output?

> db.tweets.explain("executionStats").find( { "user.followers_count" : { $gt : 1000 } } ).limit(10).skip(5000).sort( { created_at : 1 } ) { "queryPlanner" : { "plannerVersion" : 1, "namespace" : "twitter.tweets", "indexFilterSet" : false, "parsedQuery" : { "user.followers_count" : { "$gt" : 1000 } }, "winningPlan" : { "stage" : "LIMIT", "limitAmount" : 0, "inputStage" : { "stage" : "SKIP", "skipAmount" : 0, "inputStage" : { "stage" : "FETCH", "filter" : { "user.followers_count" : { "$gt" : 1000 } }, "inputStage" : { "stage" : "IXSCAN", "keyPattern" : { "created_at" : -1 }, "indexName" : "created_at_-1", "isMultiKey" : false, "direction" : "backward", "indexBounds" : { "created_at" : [ "[MinKey, MaxKey]" ] } } } } }, "rejectedPlans" : [ ] }, "executionStats" : { "executionSuccess" : true, "nReturned" : 10, "executionTimeMillis" : 563, "totalKeysExamined" : 251120, "totalDocsExamined" : 251120, "executionStages" : { "stage" : "LIMIT", "nReturned" : 10, "executionTimeMillisEstimate" : 500, "works" : 251121, "advanced" : 10, "needTime" : 251110, "needFetch" : 0, "saveState" : 1961, "restoreState" : 1961, "isEOF" : 1, "invalidates" : 0, "limitAmount" : 0, "inputStage" : { "stage" : "SKIP", "nReturned" : 10, "executionTimeMillisEstimate" : 500, "works" : 251120, "advanced" : 10, "needTime" : 251110, "needFetch" : 0, "saveState" : 1961, "restoreState" : 1961, "isEOF" : 0, "invalidates" : 0, "skipAmount" : 0, "inputStage" : { "stage" : "FETCH", "filter" : { "user.followers_count" : { "$gt" : 1000 } }, "nReturned" : 5010, "executionTimeMillisEstimate" : 490, "works" : 251120, "advanced" : 5010, "needTime" : 246110, "needFetch" : 0, "saveState" : 1961, "restoreState" : 1961, "isEOF" : 0, "invalidates" : 0, "docsExamined" : 251120, "alreadyHasObj" : 0, "inputStage" : { "stage" : "IXSCAN", "nReturned" : 251120, "executionTimeMillisEstimate" : 100, "works" : 251120, "advanced" : 251120, "needTime" : 0, "needFetch" : 0, "saveState" : 1961, "restoreState" : 1961, "isEOF" : 0, "invalidates" : 0, "keyPattern" : { "created_at" : -1 }, "indexName" : "created_at_-1", "isMultiKey" : false, "direction" : "backward", "indexBounds" : { "created_at" : [ "[MinKey, MaxKey]" ] }, "keysExamined" : 251120, "dupsTested" : 0, "dupsDropped" : 0, "seenInvalidated" : 0, "matchTested" : 0 } } } } }, "serverInfo" : { "host" : "generic-name.local", "port" : 27017, "version" : "3.0.1", "gitVersion" : "534b5a3f9d10f00cd27737fbcd951032248b5952" }, "ok" : 1 }

Homework 4.3 :

use blog db.posts.drop()
From the mac or PC terminal window
mongoimport --drop -d blog -c posts posts.json

The blog has been enhanced so that it can also display the top 10 most recent posts by tag. There are hyperlinks from the post tags to the page that displays the 10 most recent blog entries for that tag. (run the blog and it will be obvious)

Your assignment is to make the following blog pages fast:

The blog home page
The page that displays blog posts by tag (http://localhost:8082/tag/whatever)
The page that displays a blog entry by permalink (http://localhost:8082/post/permalink)
By fast, we mean that indexes should be in place to satisfy these queries such that we only need to scan the number of documents we are going to return.

To figure out what queries you need to optimize, you can read the blog.py code and see what it does to display those pages. Isolate those queries and use explain to explore.

Once you have added the indexes to make those pages fast run the following

python validate.py

(note that for folks who are using MongoLabs or MongoHQ there are some command line options to validate.py to make it possible to use those services) Now enter the validation code below.

Making the Blog fast
Please download hw4-3.zip from the Download Handout link to get started. This assignment requires Mongo 3.0 or above.

In this homework assignment you will be adding some indexes to the post collection to make the blog fast.

We have provided the full code for the blog application and you don't need to make any changes, or even run the blog. But you can, for fun.

We are also providing a patriotic (if you are an American) data set for the blog. There are 1000 entries with lots of comments and tags. You must load this dataset to complete the problem.

From the mongo shell:

Solution : 893jfns29f728fn29f20f2


Homework 4.4 :

In this problem you will analyze a profile log taken from a different mongoDB instance and you will import it into a collection named sysprofile. To start, please download sysprofile.json from Download Handout link and import it with the following command:

mongoimport --drop -d m101 -c profile sysprofile.json
Now query the profile data, looking for all queries to the students collection in the database school2, sorted in order of decreasing latency. What is the latency of the longest running operation to the collection, in milliseconds?

Solution :



Enjoy....!!!!

Feel free to comment below your experience with above approach and If you still find any problem  with above steps Let me know I would love to help you to resolve your  problem.

 If you want to take your Technological Knowledge to the Next Level and For More Technological information Stay tuned to Visionfortech


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