Ambari provides intuitive and REST APIs that automate operations in the Hadoop cluster. Its consistent and secure interface allows it to be fairly efficient in operational control. Its easy and user-friendly interface efficiently diagnoses the health of the Hadoop cluster using an interactive dashboard.

To have a better understanding of how Ambari works, let’s look at the detailed architecture of Apache Ambari in the following diagram:

Apache Ambari follows a master–slave architecture where the master node instructs the slave nodes to perform certain actions and report back the state of every action. The master node is responsible for keeping track of the state of the infrastructure. To do this, the master node uses a database server, which can be configured during the setup time.

There is a huge difference between tasks performed by these two technologies if looked closely. The following comparison will give you a clearer idea:

Therefore, though these tasks may seem similar from a distance, actually, these two technologies perform different tasks on the same Hadoop cluster making it agile, responsive, scalable, and fault-tolerant in a big way. As an Apache Ambari Administrator, you will be creating and managing Ambari users and groups. You can also import users and groups from LDAP systems into Ambari.

Apache Ambari is an open-source administration tool deployed on top of Hadoop clusters, and it is responsible for keeping track of the running applications and their status. Apache Ambari can be referred to as a web-based management tool that manages, monitors, and provisions the health of Hadoop clusters.

Introduction to Apache Ambari

It provides a highly interactive dashboard that allows administrators to visualize the progress and status of every application running over the Hadoop cluster.

Its flexible and scalable user interface allows a range of tools such as Pig, MapReduce, Hive, etc. to be installed on the cluster and administers their performances in a user-friendly fashion. Some of the key features of this technology can be highlighted as:

• Instantaneous insight into the health of the Hadoop cluster using preconfigured operational metrics
• User-friendly configuration providing an easy step-by-step guide for installation
• Installation of Apache Ambari is possible through Hortonworks Data Platform (HDP)
• Monitoring dependencies and performances by visualizing and analyzing jobs and tasks
• Authentication, authorization, and auditing by installing Kerberos-based Hadoop clusters
• Flexible and adaptive technology fitting perfectly in the enterprise environment

Hadoop ZooKeeper, is a distributed application that follows a simple client-server model where clients are nodes that make use of the service, and servers are nodes that provide the service. Multiple server nodes are collectively called ZooKeeper ensemble. At any given time, one ZooKeeper client is connected to at least one ZooKeeper server. A master node is dynamically chosen in consensus within the ensemble; thus usually, an ensemble of Zookeeper is an odd number so that there is a majority of vote. If the master node fails, another master is chosen in no time and it takes over the previous master. Other than master and slaves there are also observers in Zookeeper. Observers were brought in to address the issue of scaling. With the addition of slaves the write performance is going to be affected as voting process is expensive. So observers are slaves that do not take part into voting process but have similar duties as other slaves.

Writes in Zookeeper

All the writes in Zookeeper go through the Master node, thus it is guaranteed that all writes will be sequential. On performing write operation to the Zookeeper, each server attached to that client persists the data along with master. Thus, this makes all the servers updated about the data. However this also means that concurrent writes cannot be made. Linear writes guarantee can be problematic if Zookeeper is used for write dominant workload. Zookeeper in Hadoop, is ideally used for coordinating message exchanges between clients, which involves less writes and more reads. Zookeeper is helpful till the time the data is shared but if application has concurrent data writing then Zookeeper can come in way of the application and impose strict ordering of operations.

Reads in Zookeeper

Zookeeper is best at reads as reads can be concurrent. Concurrent reads are done as each client is attached to different server and all clients can read from the servers simultaneously, although having concurrent reads leads to eventual consistency as master is not involved. There can be cases where client may have an outdated view, which gets updated with a little delay.

Distributed applications are difficult to coordinate and work with as they are much more error prone due to huge number of machines attached to network. As many machines are involved, race condition and deadlocks are common problems when implementing distributed applications. Race condition occurs when a machine tries to perform two or more operations at a time and this can be taken care by serialization property of ZooKeeper. Deadlocks are when two or more machines try to access same shared resource at the same time. More precisely they try to access each other’s resources which leads to lock of system as none of the system is releasing the resource but waiting for other system to release it. Synchronization in Zookeeper helps to solve the deadlock. Another major issue with distributed application can be partial failure of process, which can lead to inconsistency of data. Zookeeper handles this through atomicity, which means either whole of the process will finish or nothing will persist after failure. Thus Zookeeper is an important part of Hadoop that take care of these small but important issues so that developer can focus more on functionality of the application.

Apache Zookeeper is a coordination service for distributed application that enables synchronization across a cluster. Zookeeper in Hadoop can be viewed as centralized repository where distributed applications can put data and get data out of it. It is used to keep the distributed system functioning together as a single unit, using its synchronization, serialization and coordination goals. For simplicity's sake Zookeeper can be thought of as a file system where we have znodes that store data instead of files or directories storing data. Zookeeper is a Hadoop Admin tool used for managing the jobs in the cluster. 

Definition: “It is a process of modifying surface properties of metals by the deposition of a layer of another metal or polymer on its surface or by the formation of an oxide film”.

The main technological importance of metal finishing include :-

[1] Imparting the metal surface to higher corrosion resistance.

[2] Providing electrical and thermal conducting surface.

[3] Imparting thermal resistance and hardness.

[4] In the manufacture of electrical and electronic components such as PCB’s, capacitors contacts, etc.

[5] To increase the decorativeness of metal surface. 

Nature of corrosion product

Corrosion product is always formation of oxide layer on the surface of the metal. This oxide layer act as protective film. If this product is porous, then rate of corrosion continues If the product is non-porous, rate of corrosion stops. 

Ratio of anodic to cathodic area

When anode is small and cathode is large, all the electrons liberated at anode and are consumed at the cathode. This further intensifies the anodic reaction leading to increase in overall rate of corrosion. When anode is large and cathode is small, all the electrons liberated at anode and are not consumed at the cathode. So rate of corrosion is less.  

Differential Metallic corrosion:

1. When two dissimilar metals are in direct contact with one another and exposed to a corrosive medium, the metal with lower electrode potential becomes anode and suffers from corrosion, whereas the metal with higher electrode potential becomes cathode and protected from corrosion. This type of corrosion is known as differential metal corrosion or galvanic corrosion.
2. The rate of corrosion depends mainly on the difference in the position of the two metals in galvanic series.
3. Higher the difference, faster is the rate of corrosion 

Water line corrosion:

1. It is observed in steel or iron water tank partially filled with water. Part of the tank just below water level is exposed to lower concentration of O2 becomes anodic and undergoes corrosion.
2. Part of the tank above the water line which is exposed to higher concentration of O2 becomes cathodic and protected from the corrosion.
3. More corrosion is observed just below the water line; hence this type is called water line corrosion. 

Batteries are electrochemical cells which converts chemical energy into electrical energy during discharging and charging.

•  Primary batteries: The batteries, which produce electrical energy at the expense of free energy of active materials and produce energy only as long as active materials are present, are called as primary batteries. These are nonrechargeable batteries and are to be discarded after the use. The cell reactions is said to be irreversible. Example: Dry cell. Zn-air battery.
• Secondary batteries: The rechargeable batteries that produce electrical energy at the expense of free energy of active materials are called secondary batteries. These active materials are capable of restoring at respective electrodes on recharge and prepare for discharge once again. The cell reactions is said to be reversible. Example: Lead acid battery, Ni-MH battery, Li ion battery