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Q1) What is cache fusion?

Ans. In a RAC environment, it is the combining of data blocks, which are shipped across the interconnect from remote database caches (SGA) to the local node, in order to fulfill the requirements for a transaction (DML, Query of Data Dictionary).

Q2) What is split brain?

Ans. When database nodes in a cluster are unable to communicate with each other, they may continue to process and modify the data blocks independently. If the
same block is modified by more than one instance, synchronization/locking of the data blocks does not take place and blocks may be overwritten by others in the cluster. This state is called split brain.

Q3) What is the difference between Crash recovery and Instance recovery?

Ans. When an instance crashes in a single node database on startup a crash recovery takes place. In a RAC enviornment the same recovery for an instance is performed by the surviving nodes called Instance recovery. 

Q4) What is the interconnect used for?

Ans. It is a private network which is used to ship data blocks from one instance to another for cache fusion. The physical data blocks as well as data dictionary blocks are shared across this interconnect.

Q5) How do you determine what protocol is being used for Interconnect traffic?

Ans. One of the ways is to look at the database alert log for the time period when the database was started up. 

Q6) What methods are available to keep the time synchronized on all nodes in the cluster?

Ans. Either the Network Time Protocol(NTP) can be configured or in 11gr2, Cluster Time Synchronization Service (CTSS) can be used. 

Q7) What files components in RAC must reside on shared storage?

Ans. Spfiles, ControlFiles, Datafiles and Redolog files should be created on shared storage. 

Q8) Where does the Clusterware write when there is a network or Storage missed heartbeat?

Ans. The network ping failure is written in $CRS_HOME/log 

1. What do you know about the term “Big Data”?

Ans. Big Data is a term associated with complex and large datasets. A relational database cannot handle big data, and that’s why special tools and methods are used to perform operations on a vast collection of data. Big data enables companies to understand their business better and helps them derive meaningful information from the unstructured and raw data collected on a regular basis. Big data also allows the companies to take better business decisions backed by data. 

2. What are the five V’s of Big Data?

Ans. The five V’s of Big data is as follows: 

• Volume – Volume represents the volume i.e. amount of data that is growing at a high rate i.e. data volume in Petabytes
• Velocity – Velocity is the rate at which data grows. Social media contributes a major role in the velocity of growing data.
• Variety – Variety refers to the different data types i.e. various data formats like text, audios, videos, etc.
• Veracity – Veracity refers to the uncertainty of available data. Veracity arises due to the high volume of data that brings incompleteness and inconsistency.
• Value –Value refers to turning data into value. By turning accessed big data into values, businesses may generate revenue.

Note: This is one of the basic and significant questions asked in the big data interview. You can choose to explain the five V’s in detail if you see the interviewer is interested to know more. However, the names can even be mentioned if you are asked about the term “Big Data”.

3. Tell us how big data and Hadoop are related to each other.

Ans. Big data and Hadoop are almost synonyms terms. With the rise of big data, Hadoop, a framework that specializes in big data operations also became popular. The framework can be used by professionals to analyze big data and help businesses to make decisions. 

Note: This question is commonly asked in a big data interview. You can go further to answer this question and try to explain the main components of Hadoop.

4. How is big data analysis helpful in increasing business revenue?

Ans. Big data analysis has become very important for the businesses. It helps businesses to differentiate themselves from others and increase the revenue. Through predictive analytics, big data analytics provides businesses customized recommendations and suggestions. Also, big data analytics enables businesses to launch new products depending on customer needs and preferences. These factors make businesses earn more revenue, and thus companies are using big data analytics. Companies may encounter a significant increase of 5-20% in revenue by implementing big data analytics. Some popular companies those are using big data analytics to increase their revenue is – Walmart, LinkedIn, Facebook, Twitter, Bank of America etc. 

5. Explain the steps to be followed to deploy a Big Data solution.

Ans. The first step for deploying a big data solution is the data ingestion i.e. extraction of data from various sources. The data source may be a CRM like Salesforce, Enterprise Resource Planning System like SAP, RDBMS like MySQL or any other log files, documents, social media feeds etc. The data can be ingested either through batch jobs or real-time streaming. The extracted data is then stored in HDFS.