In continuation of our discussion on data architecture covered in previous posts, let us take an example and study it. We will review Amazon Dynamo as an example of a cloud based data storage and distributed system. Dynamo addresses the need for a reliable, scalable, highly available key-value storage system. It provides the ability to trade-off cost, consistency, durability and performance while maintaining high availability. With cloud based business such as Amazon, the compute and storage is distributed in several datacenters around the world. At this scale, there are many fault domains and and yet the persistent state has to be managed with high reliability and availability. To maitain this standard, Dynamo sacrifices consistency under certain conditions It makes extensive use of object-versioning and application assisted conflict resolution.  It is used to manage the state of services that have very high reliability requirements and need tight control over the tradeoffs between availability, consistency, cost effectiveness and performance. For a store like Amazon, a relational data store is limiting in terms of scale and availability. Dynamo provides a simple primary-key interface to meet this need.
We saw how conflict resolution is handled in Dynamo. When the conflict resolution happens and who does the conflict resolution is determined by the needs of the services using Dynamo.
Other design considerations include the ability to scale out the storage with no downtime, uniform nodes and no special roles for any set of nodes, the ability to decentralize control by way of simpler scalable peers and exploit heterogeneity in infrastructure.
Peer to Peer network formed for this storage does not depend on flooding the network with queries to find the peer with the data. Instead it relies on a structure and a globally consistent protocol to ensure that any node can route the search query to some peer that has the related data.
#codingexercise
1) Given a nested list of int array – calculate the sum of all the integers, while multiplying each number by its depth…

For example:

Here’s the depth sum of the nested list {1, {2, 3}}:

{1, {2, 3}} => 1*1 + 2*2 + 3*2 = 11

Here’s the depth sum of the nested list {1, {2, {3}}}:

{1, {2, {3}}} =>  1*1 + 2*2 + 3*3 = 14

static int CalcSum(Nested n, int depth)
{
int total = n.value * depth;
if (n.IsNested())
{
int newdepth = depth++;
foreach( var nl in n.nested)
{
   total += CalcSum(nl, newdepth)
}
}
return total;
}
2) Find sentences with the highest density of words from a list : solution