Now let's talk about Amazon EMR.
So EMR stands for Elastic MapReduce
and EMR helps you create Hadoop clusters
for doing big data on AWS.
This allows you to analyze
and process vast amount of data.
Anytime you would see anything related
to big data clusters with Hadoop clusters,
then think Amazon EMR.
These clusters have to be provisioned
and they can be made of hundreds of EC2 instances.
Why would you use EMR?
EMR comes bundled with a lot of tools
that big data specialist use.
For example, Apache Spark, or HBase,
or Presto, or Apache Flink.
They're very difficult to set up,
so Amazon EMR will take care of all the provisioning
and the configuration of these services for you.
You can also auto-scale your entire cluster
and it's integrated with spot instances
for you to benefit from price reductions.
So the use cases of Amazon EMR
from an exam perspective are going to be
around data processing,
doing machine learning, web indexing and big data
but all of them using big data related technologies
such as Hadoop, Spark, HBase Preso Flink, and so on.
Amazon EMR is made of clusters of EC2 instances
and you have different kind of nodes.
You have the Master Node.
The Master Node manages the cluster,
it will coordinate and manage the health
of all your other nodes, and it must be long running.
Then you have the Core Node, they're here to run tasks
and also store data, and they must be long running as well.
Then you have this Task Node
which is there just to run tasks.
Usually you can take spot instances for it
and using task node is optional.
The purchasing options really depends.
If you have the on-demand EC2 instance type
then you're going to get reliable
predictable type of workloads
and then will never be terminated.
If you use reserved instances,
and remember it's minimum one year of usage,
then you're going to get big cost savings
and EMR will automatically
use your reserved instances if possible.
Therefore, good candidates for reserved instances
are going to be the Master Node
because it must be long running, and also the Core Nodes.
Regarding spot instances, because they can be terminated
they're less reliable but they're cheaper.
A good way for you to leverage spot instances
would be on Task Nodes.
Finally, for EMR, in terms of deployment
you can have either long running clusters
which would make sense than using reserved instances,
or you can use transient temporary clusters to
just do something and then tear it down
once the analysis is done.
Okay, you know all you need to know
for Amazon EMR, the exam.
I hope you liked it, and I will see you in the next lecture.