Okay.
Hello loggers and welcome to this lecture and this lecture.
We're going to look at redshift So what is redshift.
Well you probably remember from the databases we know one section that redshift is a way of doing business
intelligence or data warehousing in the cloud.
So Amazon Redshift is a fast and powerful fully manage petabytes scale data warehouse service in the
cloud.
And customers can start small for just 25 cents per hour with no commitments or upfront costs.
And you can scaled up to petabytes or more for a thousand dollars per terabyte per year less than one
tenth the cost of most other data warehousing solutions.
So if you need a data warehouse or redshift is the one to use it.
And certainly in terms of the top U.S. world.
So we learnt in the databases one to one the difference between online transaction processing versus
online analytics processing and online transaction processing is if you take a store you could go in
and look up a particular order and you'd look it up using an order number it's a single row of data
is online analytics processing is where you're running queries against your database and it might be
that you want the net profit for a mere and for the Pacific for digital radio product.
And this is going to pull in a huge number of records it's going to add up the sum of all radios sold
in a mere so Europe Middle East and Africa.
It's going to add up the sum of radios sold in the Pacific.
It's going to grab the unit cost of the radios in each region.
It's going to take the sales price of each radio in each region and then it's going to calculate the
sales price minus the unit cost and you can imagine the sort of queries that it's going to be running
to do this it's going to pull in data from a lot of different areas and it can put a big stress on your
database and that's why it makes sense to move your production database and to have a separate data
warehouse.
We are running these queries on so data warehousing databases actually use a different architecture
both from a database perspective as well as an infrastructure layer and Amazon's data warehouse solution
is called redshift.
So redshift can be configured as follows You can have a single node and this is 160 gigs in size or
you can have multi node and a multi node will consist of a leader node.
And this basically manages the client connections and receives queries and then you have all your compute
nodes and these store data and they perform queries and computations and you can have up to 128 different
compute nodes behind a leader node.
So redshift uses really advanced compression instead of going in and compressing individual rows inside
a table what it actually does is it compresses individual columns and because the columns contain the
same data.
So one column might be a date for example or another column might be text or might be an integer or
might be a boolean value or whatever.
When you use compression based on columns you get a lot more.
It's a lot easier to compress because all the data is the same.
So Amazon Redshift employs multiple compression techniques and can often achieve a significant compression
relative to traditional related relational database stores.
So in addition redshift doesn't require indexes or materialized views and so it uses less space than
traditional relational database systems.
And when you're loading data into an empty table Amazon Redshift automatically samples your data and
selects the most appropriate compression scheme redshift also comes with massive parallel processing
so it automatically distributes data and query loads across all your nodes.
And Richard makes it easy to add nodes to your data warehouse and enable you to maintain fast query
performance as your data warehouse grows so you can actually scale out with redshift by adding more
and more nodes behind your leader node in terms of backups redshift is comes with backups enabled by
default and they'll have a one day retention period again just like with RDX your maximum retention
period is 35 days and redshift will always attempt to maintain at least three copies of your data.
So this is the original data and a replica on the compute nodes as well as a backup in three and redshift
can also asynchronously replicate your snapshots to S3 in another region for disaster recovery redshift.
The way it's priced is basically on the compute node hours.
So this is the total number of hours you run across all your compute nodes for the billing period and
you're going to be billed for one unit per node per hour.
So 3 node data warehouse cluster running persistently for an entire month would incur twenty one of
two thousand one hundred sixty instance hours and you're not going to be charged for the leader node
hours you're only going to be charge for your compute node hours so bear that in mind as well.
And then you're also going to be charged for your backups and you're going to be charged for your data
transfer and this is only within a VPC not outside in terms of security considerations when you were
communicating with redshift it's always going to be encrypted in transit using SSL.
It's also encrypted at rest.
Using a 256 encryption and by default redshift takes cares of the key management.
You don't have to worry about managing keys with redshift but you can manage your own keys through a
hardware security module.
Also using the eight of us key management service and we do cover off cloud HCM as well as a W.S. campus
in an awful lot of detail in the certified security specialty course in terms of availability redshift
is currently only available in one Availability Zones.
You cannot have redshift with multi AC turned on just yet.
Who knows if that will change.
You can restore snapshots to a new availability zone in the event of an outage and then just onto my
exam tips.
Just remember that redshift is used for business intelligence.
It's only available in one AC and in terms of backups it's enabled by default with a one day retention
period annual maximum retention period is 35 days and then redshift will always attempt to maintain
at least three copies of your data the original and the replica on the compute nodes as well as a backup
in Amazon S3 and redshift can also asynchronously replicate your snapshots to S3 in another region for
disaster recovery.
So that is it for this lecture guys.
If you have any questions please let me know.
If not feel free to move on to the next lecture where we're going to cover off Amazon's Aurora.