1618615260
MongoDB Aggregation vs MapReduce in a Sharded setup on Docker containers
Exploring the world of MapReduce, I landed on the MapReduce documentation page of MongoDB. The first thing that is mentioned there is
An aggregation pipeline provides better performance and usability than a map-reduce operation.
So here I am thinking - “should I carry-on exploring the MapReduce method of MongoDB or dive a little deep into Aggregation Pipeline?”. For my self-satisfaction, I finally thought that it would be interesting to juxtapose MapReduce with Aggregation Pipeline and compare them. In this read, I write about how I did the same with regards to CPU and memory utilization when performing a simple query over a large data set and see which one presented the result faster.
The problem statement — Counting the Swedish pronouns “den”, “denne”, “denna”, “det”, “han”, “hon” and “hen” (case-insensitive) in Twitter tweets. How many tweets? — Approximately 4 million tweets.
When following a simple approach of running MapReduce and Aggregation Pipeline code for the above problem on a single small VM (4 GB RAM and 2 vCPUs), the MapReduce job gave the result in around ~8mins while Aggregation Pipeline gave the same in ~5mins.
#docker #mongodb #mapreduce
What is GEEK
Buddha Community
1618615260
MongoDB Aggregation vs MapReduce in a Sharded setup on Docker containers
Exploring the world of MapReduce, I landed on the MapReduce documentation page of MongoDB. The first thing that is mentioned there is
An aggregation pipeline provides better performance and usability than a map-reduce operation.
So here I am thinking - “should I carry-on exploring the MapReduce method of MongoDB or dive a little deep into Aggregation Pipeline?”. For my self-satisfaction, I finally thought that it would be interesting to juxtapose MapReduce with Aggregation Pipeline and compare them. In this read, I write about how I did the same with regards to CPU and memory utilization when performing a simple query over a large data set and see which one presented the result faster.
The problem statement — Counting the Swedish pronouns “den”, “denne”, “denna”, “det”, “han”, “hon” and “hen” (case-insensitive) in Twitter tweets. How many tweets? — Approximately 4 million tweets.
When following a simple approach of running MapReduce and Aggregation Pipeline code for the above problem on a single small VM (4 GB RAM and 2 vCPUs), the MapReduce job gave the result in around ~8mins while Aggregation Pipeline gave the same in ~5mins.
#docker #mongodb #mapreduce
1608388622
Query of MongoDB | MongoDB Command | MongoDB | Asp.Net Core Mvc
#mongodb tutorial #mongodb tutorial for beginners #mongodb database #mongodb with c# #mongodb with asp.net core #mongodb
1602317778
Ever Wondered Why We Use Containers In DevOps?
At some point we’ve all said the words, “But it works on my machine.” It usually happens during testing or when you’re trying to get a new project set up. Sometimes it happens when you pull down changes from an updated branch.
Every machine has different underlying states depending on the operating system, other installed programs, and permissions. Getting a project to run locally could take hours or even days because of weird system issues.
The worst part is that this can also happen in production. If the server is configured differently than what you’re running locally, your changes might not work as you expect and cause problems for users. There’s a way around all of these common issues using containers.
What is a container
A container is a piece of software that packages code and its dependencies so that the application can run in any computing environment. They basically create a little unit that you can put on any operating system and reliably and consistently run the application. You don’t have to worry about any of those underlying system issues creeping in later.
Although containers were already used in Linux for years, they became more popular in recent years. Most of the time when people are talking about containers, they’re referring to Docker containers. These containers are built from images that include all of the dependencies needed to run an application.
When you think of containers, virtual machines might also come to mind. They are very similar, but the big difference is that containers virtualize the operating system instead of the hardware. That’s what makes them so easy to run on all of the operating systems consistently.
What containers have to do with DevOps
Since we know how odd happenings occur when you move code from one computing environment to another, this is also a common issue with moving code to the different environments in our DevOps process. You don’t want to have to deal with system differences between staging and production. That would require more work than it should.
Once you have an artifact built, you should be able to use it in any environment from local to production. That’s the reason we use containers in DevOps. It’s also invaluable when you’re working with microservices. Docker containers used with something like Kubernetes will make it easier for you to handle larger systems with more moving pieces.
#devops #containers #containers-devops #devops-containers #devops-tools #devops-docker #docker #docker-image
1608388501
Install MongoDB Database | MongoDB | Asp.Net Core Mvc
#MongoDB
#Aspdotnetexplorer
#mongodb #mongodb database #mongodb with c# #mongodb with asp.net core #mongodb tutorial for beginners #mongodb tutorial
1597368540
Docker Tutorial for Beginners 8 - Build and Run C++ Applications in a Docker Container
Docker is an open platform that allows use package, develop, run, and ship software applications in different environments using containers.
In this course We will learn How to Write Dockerfiles, Working with the Docker Toolbox, How to Work with the Docker Machine, How to Use Docker Compose to fire up multiple containers, How to Work with Docker Kinematic, Push images to Docker Hub, Pull images from a Docker Registery, Push stacks of servers to Docker Hub.
How to install Docker on Mac.
#docker tutorial #c++ #docker container #docker #docker hub #devopstools