What are the differences between AWS EC2 and EMR?

What are the differences between AWS EC2 and EMR?

Amazon EC2 is a cloud based service which gives customers access to a varying range of compute instances, or virtual machines. Amazon EMR is a managed big data service which provides pre-configured compute clusters of Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto.

What is AWS Elastic Map Reduce?

Amazon EMR (previously called Amazon Elastic MapReduce) is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark , on AWS to process and analyze vast amounts of data.

Which scenario is useful for running an Amazon EMR cluster with low redundancy?

Q: When would I use Inf1 vs. C6i or C5 vs. G4 instances for inference?

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Model Characteristics and Libraries Used EC2 Inf1 EC2 G4
Models that benefit from low latency and high throughput at low cost X
Models not sensitive to latency and throughput
Models requiring NVIDIA’s developer libraries X

How does EMR cluster work?

The node types in Amazon EMR are as follows: Master node: A node that manages the cluster by running software components to coordinate the distribution of data and tasks among other nodes for processing. The master node tracks the status of tasks and monitors the health of the cluster.

When should I use Amazon EMR?

Use EMR (SparkSQL, Presto, hive) when

  1. When you dont need a cluster 24X7.
  2. When elasticity is important (auto scaling on tasks)
  3. When cost is important: spots.
  4. Until a few hundred TB’s, In some cases PB’s will work.
  5. When you want to separate compute and storage (external table + task node + auto scaling)

How can you create Hadoop clusters to analyze and process a vast amount of data?

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Launch a fully functional Hadoop cluster using Amazon EMR. Define the schema and create a table for sample log data stored in Amazon S3. Analyze the data using a HiveQL script & write the results back to Amazon S3. Download and view the results on your computer.

Why does an Elastic MapReduce?

Elastic MapReduce helps the company to sort and process large amounts of internal data. Elastic MapReduce is based on the MapReduce function, an element of the traditional Hadoop software. Hadoop and its accessories are open-source parts of a system for dealing with big data.

What is the best distribution for Hadoop on AWS?

Primarily, you can choose between Cloudera distribution on EC2 and Amazon EMR distribution as your Hadoop cluster on AWS. Each option has its own set of advantages and limitations. EMR segregates slave nodes into two subtypes – Core Nodes and Task nodes.

What are the basic concepts about Amazon ECS clusters?

The following are general concepts about Amazon ECS clusters. Clusters are Region-specific. The following are the possible states that a cluster can be in. The cluster is ready to accept tasks and, if applicable, you can register container instances with the cluster.

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Does EMR benefit from the Hadoop file system?

The way most folks use EMR they don’t benefit from the Hadoop File System. Most use cases involve storing data for use on EMR on Amazon’s S3 which has a higher latency and does not locate the data on your computational nodes. So file IO on EMR is slower and more latent than IO on your own Hadoop cluster or on your own EC2 cluster.

What is emrfs in AWS S3?

EMRFS is an implementation of HDFS used for reading and writing regular files from Amazon EMR directly to Amazon S3. Giving an option to separate out storage completely from compute is theoretically awesome and does not require us to spin up EC2 instances or provision EBS volumes just to add more storage.