We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the throughput of ZooKeeper when the system is saturated and with various injected failure.The most dip in throughput occurred with the failures of the leader. On the other hand, failure of the followers is tolerated with a quorum and the leader election algorithm helps mitigate this further.
We now start reading "Modern data Fraud Prevention at Big Data Scale". Feedzai enables companies to move from broad segment based scoring of transactions to individual oriented scoring with machine learning based techniques.Traditional approaches such  as those based on SAS suffered from the limitation that they have become old and difficult to maintain. Second, they are inflexible and unable to keep up with dynamic requirements.Feedzai claims to use a new technology on a new platform. They claim to have highest fraud detection rates with lowest false positives. They have true real time processing. They have true machine learning capabilities. They run on commodity hardware. They are non-intrusive and they are easily deployed.
we will read about them in the coming week. But I have a question to ask will fraud detection go down if we can differentiate that the transaction was indeed made by the genuine user ? do we always need the user to sign in to let us know that he or she is the real user. Will we recognize them by the phone they carry. we allow websites to delegate authentication such as with OAuth. Why don't we delegate it to Androids and  Apple's ?

#Fraud detection service introduction: https://1drv.ms/w/s!Ashlm-Nw-wnWsEv9woJ7ynzJAPpv 

#codingexercise
any contiguous sorted collection with duplicates has linear runtime complexity to find the weighted mean

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the throughput of ZooKeeper when the system is saturated and with various injected failure.The most dip in throughput occurred with the failures of the leader. On the other hand, failure of the followers is tolerated with a quorum and the leader election algorithm helps mitigate this further.
The latency of requests was also measured. The requests processed per second seemed to increase with the number of the workers but decrease with the number of servers. The average request latency was  found to be between 1.2ms - 1.4 ms.
We conclude with discussion of related work as cited by the authors.  They mention Chubby which also uses a file system interface and an agreement protocol to guarantee the replicas but it is a lock service. Clients using ZooKeeper can choose to implement locks. Also Chubby only allows clients to connect to the leader and not with any other server. ZooKeeper has better performance and a more relaxed consistency model
Some systems focus on fault-tolerance such as ISIS which transforms abstract type specifications into fault tolerant distributed objects thus making fault tolerance mechanism transparent to users.  Other systems like Totem guarantee order of messages in an architecture that exploits hardware broadcasts of local area networks. ZooKeeper also implements the notion of synchronization on a virtual timeline and ordering of requests. ZooKeeper also supports a variety of network topology.
Some systems utilize a state machine replication as for example, Paxos that combines transaction logging for consensus with write-ahead logging for data recovery Some replicated state machines are fully Byzantine tolerant. ZooKeeper is not so but it can be made one without modifying the server code.  Boxwood uses Paxos to form a distributed lock service but it is a higher level primitive while ZooKeeper does not restrict clients from having different primitives. Sinfonia introduced mini-transactions . a new paradigm for building scalable distributed systems. Sinfonia has been designed to store application data but ZooKeeper stores application metadata.Moreover ZooKeeper can add watches where as Sinfonia cannot.  Dynamo  allows clients to put data in a distributed key - value store. The key space in Dynamo is not hierarchical unlike ZooKeeper which also provides better consistency and durability guarantees.
#codingexercise
Find the number of elements who have the same minimum number of duplicates in a contiguous sorted sequence
Solution:
        1. For each element in a contiguous sequence
        2.        Insert the element, count of repetitions in a dictionary
        3. Find the min count from the values in a dictionary
        4. for each key-value pair in the dictionary
                  if the value == min count
                      print the key

This can be improved without use of a hash table by retaining only a single key value pair that is updated when the value is lower than the previous. A count is maintained for every match with the key value pair and reset when the key value pair changes.
#Fraud detection service introduction: https://1drv.ms/w/s!Ashlm-Nw-wnWsEv9woJ7ynzJAPpv 

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the throughput of ZooKeeper when the system is saturated and with various injected failure.It was seen that the throughput tanked for failure and recovery of a follower, failure and recovery of a different follower, failure of the leader, failure of the two followers in the first two marks and recovery at the third mark, and recovery of the leader. The most dip in throughput occurred with the failures of the leader. On the other hand, failure of the followers is tolerated with a quorum and therefore the throughput falls only as much as the failing read requests Also the leader election algorithm helps mitigate this further. Third even if the followers take more time to recover, ZooKeeper is able to raise the throughput with the distribution of the load after recovery.
The latency of requests was also measured. A worker process creates and deletes new node except that the deletes are asynchronous. The number of worker process is varied but a large number of nodes are attempted. The requests processed per second seemed to increase with the number of the workers but decrease with the number of servers. The average request latency was  found to be between 1.2ms - 1.4 ms.
A number of barriers was also executed sequentially to evaluate the behavior of primitives with ZooKeeper. For each barrier like a mutex, a client waits for all other clients before moving on to the instruction succeeding it. This is true for both entry and exit. The number of barriers were executed one after the other.  The time to process the barriers increased linearly with the number of barriers which indicated that the concurrent access to the data tree does not hamper the execution.  Also, the latency increased proportionally to the number of clients.
#codingexercise
Find the number of elements who have the same maximum number of duplicates in a contiguous sorted sequence
Solution:
        1. For each element in a contiguous sequence
        2.        Insert the element, count of repetitions in a dictionary
        3. Find the max count from the values in a dictionary
        4. for each key-value pair in the dictionary
                  if the value == max count
                      print the key

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the throughput of ZooKeeper when the system is saturated and changes on various injected failure. A large number of clients connected and this number was kept the same while the servers were varied. This simulated a large load and it was seen that the number of servers had a negative impact on performance. Read throughput is consistently higher than write throughput.Write requests had to go through atomic broadcast. Transactions are logged to non-volatile store. These contribute to the difference in throughput.
In production systems, some performance is traded off for reliability especially because ZooKeeper is the source of truth for applications. More servers are used to tolerate more faults and partition write throughput. Load can be distributed because ZooKeeper has relaxed consistency guarantee. If all the requests were to be directed towards the leader, the read throughput goes down and even the write throughput is lower. This can be explained as the diminished ability of the leader to perform the atomic broadcast operations while servicing all requests. In fact, atomic broadcast is the only true limiting factor for the ZooKeeper. To measure this, the requests are all directed towards the leader  and the system is saturated. The broadcast protocol becomes CPU bound at maximum throughput  It is not the same as the performance with all write requests because some work goes towards client communication, ACL checks and transaction conversions.As mentioned earlier, some performance is traded off in favor of correctness and reliability but that said the authors stated that there is room for improvement with elimination of extra copies, multiple serializations and efficient internal data structures.
The experiments performed by the authors also included injecting failures such as killing server processes. For this the write requests were maintained at 30%.  It was seen that the throughput tanked for failure and recovery of a follower, failure and recovery of a different follower, failure of the leader, failure of the two followers in the first two marks and recovery at the third mark, and recovery of the leader. The most dip in throughput occurred with the failures of the leader. On the other hand, failure of the followers is tolerated with a quorum and therefore the throughput falls only as much as the failing read requests Also the leader election algorithm helps mitigate this further. Third even if the followers take more time to recover, ZooKeeper is able to raise the throughput with the distribution of the load after recovery.

#codingexercise
Given a list of 1s and 0s and an integer m, find the positions of upto m zeros which when flipped gives the maximum contiguous 1s.

void PrintPositions(List<int> A, int m)
{
// sliding window boundaries
int l = 0;
int r = 0;
// solution involving best size and boundaries
int best = INT_MIN;
int start = 0;
int end = 0;
// count of zeros
int c = 0;
while (r < A.Count)
{
if ( c <= m)
{
   r++;
   if (A[r] == 0) c++;
}
if (c > m)
{
   if (A[l] == 0) c--;
   l++;
}
if ( r - l > best)
{
best = r - l;
start = l;
end = r;
}
}
if ( best > INT_MIN)
{
   Console.WriteLine();
   for (int i = start; I <= end; I++)
        if (A[I] == 0)
            Console.Write("{0} ", i);
   Console.WriteLine();
}
}

In the above sliding window, we can also eliminate one of the best, start and end variables.

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the throughput of ZooKeeper when the system is saturated and changes on various injected failure. A large number of clients connected and this number was kept the same while the servers were varied. This simulated a large load and it was seen that the number of servers had a negative impact on performance. Read throughput is consistently higher than write throughput.Write requests had to go through atomic broadcast. Transactions are logged to non-volatile store. These contribute to the difference in throughput.

#codingexercise
Find three elements in an array that satisfy Pythagorean theorem
Solution:
        1. Square all the elements
        2. Sort all the squares
        3. For every element from the end as item
                  Iterate from start to the element just previous to this item as candidate
                            let difference = item - candidate
                                 if difference >= candidate and difference exists between candidate and item by binary_search
                                     return Tuple<int, int, int> as candidate, difference, item

Software for  Email Campaign updated: https://1drv.ms/w/s!Ashlm-Nw-wnWsEXQ3UmFVYv0GpFe  

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the durability guarantee of ZooKeeper. On every read request, a zxid is returned that relates to the last transaction seen by the server. Since the writes are all transactional, this zxid indicates a partial order of the read requests.  If a client connects to a different server, that server ensures that its view of the ZooKeeper data is at least as current as that of the client by comparing its zxid with that of the client. If the client is more recent, the server does not reestablish a session until it has caught up. Since a majority of the ZooKeepers would be current before the client received the zxid, the client is guaranteed to find another server that has a recent view of the system.
Client session failures are detected using timeouts. The leader determines that the client is gone if none of the servers received anything within the timeout. The client is encouraged to send a heartbeat if there are no active requests for a long time. This is automatically done in the client library from ZooKeeper.
The evaluations done with ZooKeeper by the authors included measuring throughput when the system is saturated and changes on various injected failure. A large number of clients connected and this number was kept the same while the servers were varied. This simulated a large load and it was seen that the number of servers had a negative impact on performance. Read throughput is consistently higher than write throughput.Write requests had to go through atomic broadcast. Transactions are logged to non-volatile store. These contribute to the difference in throughput.

Software for  Email Campaign updated: https://1drv.ms/w/s!Ashlm-Nw-wnWsEXQ3UmFVYv0GpFe  

We continue discussing the ZooKeeper. It is a co-ordination service with elements from group messaging, shared registers and distributed lock services. It provides a interface that guarantees wait-free property and FIFO execution of requests from each client.  Requests across all clients are also linearized.
We were discussing the components of ZooKeeper - the request processor, the atomic broadcast and the replicated database. The request processor is one which prepares the request for processing that also includes co-ordination activities among servers for write requests. If the request processing involves co-ordination, it is handled by an agreement protocol which is an implementation of atomic broadcast. The changes are committed in ZooKeeper database that is replicated across all servers.  This database is periodically snapshot because replaying all the messages in order would take too long to recover state. During the snapshot, the ZooKeeper state is not locked so the snapshots don't really reflect the state of the ZooKeeper at any point of time. However since the transactions are idempotent, snapshots allow the state to be restored because the changes can be applied more than once and they are in the same order as in replay.
We will now see how ZooKeeper provides durability.  On every read request, a zxid is returned that relates to the last transaction seen by the server. Since the writes are all transactional, this zxid indicates a partial order of the read requests. All responses including the heartbeats during periods of idle activity include the last zxid seen by the server that the client is connected to. If a client connects to a different server, that server ensures that its view of the ZooKeeper data is at least as current as that of the client by comparing its zxid with that of the client. If the client is more recent, the server does not reestablish a session until it has caught up. Since a majority of the ZooKeepers would be current before the client received the zxid, the client is guaranteed to find another server that has a recent view of the system. This gurantees durability. ZooKeeper also maintains a session timeout to detect client  session failures. Generally clients re-establish a session. The client library for ZooKeeper actually sends client heartbeats and switches servers if the servers are not responsive enough.
Software for  Email Campaign: https://1drv.ms/w/s!Ashlm-Nw-wnWsEXQ3UmFVYv0GpFe  
#codingexercise
Another method for finding the number of duplicates in a sorted contiguous sequence is similar to the earlier  binary search based method of traversing linearly from the current element but searching for the previous and next elements instead.