The Effects of India’s Currency Reform?


Plenty of Indians do use cash transactions to hide their wealth and avoid taxes — less than 3 percent of the population pays income taxes — and the authorities occasionally arrest businesspeople or corrupt officials with currency hoards that can fill trucks. But plenty more people use cash because of habit, poverty or a lack of easy access to banks.

So instead of just aiming squarely at wealthy tax dodgers, the demonetization is also hammering the poor, the working-class and small business people whose lives have been turned upside down during the transition to new currency notes.

A research report this week from the banking giant HSBC predicted that imports of consumer goods would fall, but added that could be offset by a spike in demand for gold, as unsettled Indians look for ways to store their wealth.

In worst-case scenarios, the effects of demonetization could last for years, driving the country into recession and pushing Indians to keep their wealth in more stable currencies, such as the euro or U.S. dollar.

Raghuram Rajan, the former head of India’s central bank and one of the country’s most respected economists, warned in 2014 that demonetization programs can easily stumble.

“It’s not that easy to flush out black money,” he said after a speech, while he was still the country’s top banker. He added, “my sense is that the clever find ways” to get around currency overhauls.

Rajan has instead suggested better monitoring of financial transactions, such as using government ID cards to track major purchases, and improved tax enforcement.

Prabal Chakraborty


Technical differences between Pig Hadoop and Hive Hadoop


With the advent of various technologies the data is growing exponentially. This exponential growing data with various variety, huge volume, different veracity and value is categorized into 3 types namely Structured Data, Semi Structured Data, quasi structured and Unstructured Data. Structured Data is nothing but data that can be stored in databases, for instance, the transaction records of any online purchase that you make can be stored in a database whereas data that can only be partially stored in the database is referred to as semi structured data, for instance, the data that is present in the XML records can be stored partially in the database. Any other form of data that cannot be categorized as Structured or semi-structured is referred to as Unstructured Data, for instance, the data from Social Networking websites or the web logs which cannot be analyzed or stored for processing in the databases are examples of unstructured data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

Apache Hadoop is an excellent framework for processing, storing and analyzing large volumes of unstructured data known as Big Data. Hadoop technology is the buzz word as deals with big data that runs into Tera bytes, petabytes, and zeta bytes these days with various key components that comprise the Hadoop Ecosystem. It typically serves two purposes:

  1. Storing enormous amounts of data: This is achieved by partitioning the data among several nodes.
    Block-size in Hadoop File System is also much larger (64 or 128 MB) than normal file-systems (64kb).
  1. Bringing computation to data: Traditionally, data is brought to clients for computation.
    But data stored in Hadoop is so large that it is more efficient to do the opposite.
    This is done by writing map-reduce jobs which run closer to the data stored in the Hadoop.

Hadoop Ecosystem comprises of many components like Map Reduce Framework,HDFS (Hadoop Distributed File System),Hive, HBase, Pig,Flume,Sqoop,Oozie, Zoo Keeper, Ambari,Avro,Mahaout,HCatalog, Storm, Big Top , Solr Lucene ,Spark. Among all the two major key components of Hadoop Ecosystem are Hive and Pig.

  1. HIVE Hadoop


Hive Hadoop was founded by Jeff Hammerbacher who was working with Facebook.  When working with Facebook he realized that they receive huge amounts of data on a daily basis and there needs to be a mechanism which can store, mine and help analysis of the data. This idea to mine and analyze huge amounts of data gave birth to Hive. It is Hive that has enabled Facebook to deal with 10’s of Terabytes of Data on a daily basis with ease.

About Hive:  Hive is similar to a SQL Interface in Hadoop, Hive select, where, group by, and order by clauses are similar to SQL for relational databases.  Hive loses some ability to optimize the query, by relying on the Hive optimizer.  The data that is stored in HBase component of the Hadoop Ecosystem can be accessed through Hive. Hive is of great use for developers who are not well-versed with the MapReduce framework for writing data queries that are transformed into Map Reduce jobs in Hadoop.

Hive is considered as a Data Warehousing package that is constructed on top of Hadoop for analyzing huge amounts of data. Hive is mainly developed for users who are comfortable in using SQL. The best thing about Hive is that it conceptualizes the complexity of Hadoop because the users need not write MapReduce programs when using Hive so anyone who is not familiar with  Java Programming and Hadoop API’s can also make the best use of Hive.



Hence Hive Hadoop in points can be summarized as:

  • A Data Warehouse Infrastructure
  • Definer of a Query Language popularly known as HiveQL (similar to SQL)
  • Provides us with various tools for easy extraction, transformation and loading of data.
  • Hive allows its users to embed customized mappers and reducers.

Hive Hadoop is very much popular because of following reasons:

  • Hive Hadoop provides the users with strong and powerful statistics functions.
  • Hive Hadoop is like SQL, so for any SQL developer the learning curve for Hive will almost be negligible.
  • Hive Hadoop can be integrated with HBase for querying the data in HBase whereas this is not possible with Pig. In case of Pig, a function named HbaseStorage () will be used for loading the data from HBase.
  • Hive Hadoop has gained popularity as it is supported by Hue.
  • Hive Hadoop has various user groups such as CNET,, Facebook, and Digg and so on.
  1. PIG Hadoop

History: Pig Hadoop was developed by Yahoo in the year 2006 so that they can have an ad-hoc method for creating and executing MapReduce jobs on huge data sets. The main motive behind developing Pig was to cut-down on the time required for development via its multi query approach. Pig is a high level data flow system that renders you a simple language platform popularly known as Pig Latin that can be used for manipulating data and queries. Pig is used by Microsoft, Yahoo and Google, to collect and store large data sets in the form of web crawls, click streams and search logs. Pig at times finds its usage in ad-hoc analysis and processing of information.

What makes Pig Hadoop popular?

  • Pig Hadoop follows a multi query approach thus it cuts down on the number times the data is scanned.
  • Pig Hadoop is very easy to learn read and write if you are familiar with SQL.
  • Pig provides the users with a wide range of nested data types such as Maps, Tuples and Bags that are not present in MapReduce along with some major data operations such as Ordering, Filters, and Joins.
  • Performance of Pig is on par with the performance of raw Map Reduce.
  • Pig has various user groups for instance 90% of Yahoo’s MapReduce is done by Pig, 80% of Twitter’s MapReduce is also done by Pig and various other companies such as Sales force, LinkedIn, AOL and Nokia also employ Pig.

Benefits of Pig Hadoop and Hive Hadoop: Pig Hadoop and Hive Hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. However, when to use Pig Latin and when to use HiveQL is the question most of the developers have. Instead of writing Java code to implement MapReduce, one can opt between Pig Latin and Hive SQL languages to construct MapReduce programs. Benefit of coding in Pig and Hive is – much fewer lines of code, which reduces the overall development and testing time. Pig Latin has many of the usual data processing concepts that SQL has, such as filtering, selecting, grouping, and ordering, but the syntax is a little different from SQL.Hive is commonly used at Facebook for analytical purposes.  Facebook promotes the Hive language. However, Yahoo! is a big advocate for Pig Latin.  Yahoo! has one of the biggest Hadoop clusters in the world.  Their data engineers use Pig for data processing on their Hadoop clusters. Alternatively, you may choose one among Pig and Hive at your organization, if no standards are set. Data engineers have better control over the dataflow (ETL) processes using Pig Latin, especially with procedural language background. A data analyst finds that one can ramp up on Hadoop faster, by using Hive, especially with previous experience of SQL.  If you really want to become a Hadoop expert, then you should learn both Pig and Hive for the ultimate flexibility.

Differences between Pig and Hive- Depending on the purpose and type of data you can either choose to use Hive Hadoop component or Pig Hadoop Component based on the below differences :

1) Hive Hadoop Component is used mainly by data analysts whereas Pig Hadoop Component is generally used by Researchers and Programmers.

2) Hive Hadoop Component is used for completely structured Data whereas Pig Hadoop Component is used for semi structured data.

3) Hive Hadoop Component has a declarative SQLish language (HiveQL) whereas Pig Hadoop Component has a procedural data flow language (Pig Latin)

4) Hive Hadoop Component is mainly used for creating reports whereas Pig Hadoop Component is mainly used for programming.

5) Hive Hadoop Component operates on the server side of any cluster whereas Pig Hadoop Component operates on the client side of any cluster.

6) Hive Hadoop Component is helpful for ETL whereas Pig Hadoop is a great ETL tool for big data because of its powerful transformation and processing capabilities.

7) Hive can start an optional thrift based server that can send queries from any nook and corner directly to the Hive server which will execute them whereas this feature is not available with Pig.

8) Hive directly leverages SQL expertise and thus can be learnt easily whereas Pig is also SQL-like but varies to a great extent and thus it will take some time efforts to master Pig.

9) Hive makes use of exact variation of the SQL DLL language by defining the tables beforehand and storing the schema details in any local database whereas in case of Pig there is no dedicated metadata database and the schemas or data types will be defined in the script itself.

10) The Hive Hadoop component has a provision for partitions so that you can process the subset of data by date or in an alphabetical order whereas Pig Hadoop component does not have any notion for partitions though might be one can achieve this through filters.

11) Pig supports Avro whereas Hive does not.

12) Pig can be installed easily over Hive as it is completely based on shell interaction

13) Pig Hadoop Component renders users with sample data for each scenario and each step through its “Illustrate” function whereas this feature is not incorporated with the Hive Hadoop Component.

14) Hive has smart inbuilt features on accessing raw data but in case of Pig Latin Scripts we are not pretty sure that accessing raw data is as fast as with HiveQL.

15) You can join, order and sort data dynamically in an aggregated manner with Hive and Pig however Pig also provides you an additional COGROUP feature for performing outer joins.

There is no battle between HIVE and PIG in the real world. They don’t have the same advantages and disadvantages while processing enormous amounts of data. It’s just the initial ambiguity on deciding the tool which suits the need. HIVE Query language (HiveQL) suits the specific demands of analytics meanwhile PIG supports huge data operation. PIG was developed as an abstraction to avoid the complicated syntax of Java programming for MapReduce. On the other hand HIVE QL is based around SQL, which makes it easier to learn for those who know SQL. AVRO is supported by PIG making serialization faster. When it really boils down on taking decision between Pig and Hive, the suitability of the each component for the given business logic must be considered and then the decision must be taken.

Conclusion: To conclude with after having understood the difference between Pig and Hive, both Hive Hadoop and Pig Hadoop Component will help to achieve the same goals, we can say that Pig is a script kiddy and Hive comes in, innate for all the natural database developers. When it comes to access choices, Hive is said to have more features over Pig. Both the Hive and Pig components are reportedly having near about the same number of committers in every project and likely in the near future we are going to see great advancements in both on the development front.


Arpana Chaturvedi

Asst. Prof (Dept. Of IT)

Badshah’s Night


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Jims in association with Rotary District 3012 and Rotary club of Delhi Nirvana organised  a  star night at Tyagraj Stadium .JIMS grooved to the moves of famous singer Badshah popular numbers .

Certificate Distribution


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Honorable chairman , Dr. Amit Gupta presented certificates , on the occasion of half yearly merit certificate distribution ceremony ,  to those who have done well in various subjects. He congratulated the students for their good performance and ask them to remain committed to their goals .

Is Diwali the Festival of Lights Or Crackers?


Now a days, people burn dangerous fire crackers limitlessly. Crackers have big hand in polluting our environment. The toxic substances used in the firecrackers release toxic gases that are harmful to the health of all living beings. The noise of the crackers cause immense suffering to birds and animals. Diwali is the festival of lights and not burning of the limitless crackers which takes the form of air and noise pollution. We should minimize the use of firecrackers during diwali celebrations and other celebrations. Noiseless diwali has become the concept for the last few years. It is slowly gathering momentum too. But it has not yet reached that level to which we all can say that yes, we celebrated a noiseless safe and pollution free diwali. A festival must be treated like a festival not like enjoyment or nuisance. There is no need to pollute the environment for this. We must take steps to make ourselves and others aware to put an end to noise through rallies and hoardings. We must not buy unlimited crackers instead of that we can help a poor with that money. These days, trend of diwali greetings, diwali messages, diwali cards, diwali ecards, diwali calendar, diwali greeting cards, diwali flash, diwali themes, diwali screensaver, diwali images, diwali rangoli, diwali scraps, diwali designs, diwali painting is going on. It seems and feels very nice to wish each other by different means. But we must also make each other aware of the harms of the pollution caused by the firecrackers that leads directly or indirectly to global warming.


Air Pollution

A heavy smog hangs low in the air on Diwali night and a few days after that. While we ignore the smell – and some even claim to like it – we can’t ignore the fact that we are inhaling poison. The levels of sulphur nitrates, magnesium, nitrogen dioxide increase, and these chemicals are injurious to our respiratory passages. Asthamatics, beware! Diwali can be potentially fatal!

Noise Pollution

‘Bombs’ are a favourite amongst kids, and the noisier the better. This leads to noise pollution, and a prolonged exposure to such high levels of noise can lead to permanent damage of the eardrums.

The amount of garbage released on the day after Diwali is phenomenal. Approximately 4,000 additional metric tonnes of garbage are released in Delhi alone, and twice the amount in Mumbai. And this garbage, far from being eco-friendly, is extremely hazardous for the environment as it comprises of chemicals like phosphorous, sulphur and potassium chlorate, and tonnes of burnt paper.

Numerous fire accidents occur every year. Rough estimates claim that nearly 10,000 people get injured by the crackers. Most of the injuries are minor, but cause an untold amount of pain. Most of the victims are children in the age group of 8-16.

Eco sensitive Initiatives around Diwali

With the growing recognition of the impacts of Diwali on the environment, several groups have started to reinterpret the rituals and traditions to become more sensitive to nature. For instance, the children of NCL school, Pune celebrate a different Diwali by sharing clothes with the lesser privileged.

This Diwali to be more polluted than last two years


According to System of Air Quality and Weather Forecasting and Research (SAFAR) of the Ministry of Earth Science, the air quality in the National Capital Region will be “severe” on October 30 and 31 and “worst” on October 31.

The Air Quality Index (AQI) will be 443 on Sunday, or the Diwali day, and reach 472 the day after. AQI between 300 to 400 is rated as very poor, and above 400 is rated as severe.

“The highest levels of PM10 and PM2.5 (particulate matter) are expected between 11 a.m. and 3 p.m. on the night of October 30 and 31. The air quality will be worst on October 31 and will start to improve from November 1,” says the SAFAR forecast.

There is enough moisture in the air and winds are stagnant, and atmospheric holding capacity of the emissions coming from firecrackers has increased, it said.

According to SAFAR, PM 2.5 particulate concentration in the air on Diwali is likely to be around 322 micrograms per cubic meter as compared to 217 micrograms on Diwali last year and 260 micrograms in 2014.

While PM10 or particulate matter between 2.5 to 10 micrometers in diameter usually emanates from crushing or grinding operations and dust stirred up by vehicles on roads, PM2.5, particulate matter 2.5 micrometers or less in diameter, are produced from all types of combustion, including motor vehicles, power plants, residential wood burning, forest fires, agricultural burning, and some industrial processes.

As per SAFAR health advisory, when the AQI is severe, people should avoid all physical activity outdoors.

Incidentally, the levels of particulate matter were significantly low in 2016 as compared to 2014 and 2015, but since October 25, started to become significantly higher.

Delhi Pollution Control Committee’s (DPCC) senior scientist M.P. George attributed paddy stubble burning in Punjab and Haryana as the chief reason for this year’s Diwali being more polluted than 2014 and 2015.

The state environment department has also seized illegally imported crackers in several parts of the city.

Toxic smog covers Delhi after Diwali

Delhi has been blanketed in a toxic fog the morning after the Hindu festival of Diwali, when hundreds of thousands of people in the Indian capital celebrate by setting off crackers and fireworks.

Air quality in the Indian capital, one of the world’s most polluted cities, is usually very poor due to road dust, open fires, vehicle exhaust fumes, industrial emissions and the burning of crop residues in neighbouring states.

But the density of some harmful particles and droplets in the air spikes for days after Diwali and can reach up to 42 times the safe limit.


Nishi Aggarwal



National Media Seminar


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Jims organised  11th National Media Seminar on the topic “Radio as people’s mass media in post liberalized India” on October 26, 2016, at IIMC Auditorium (MANCH). . The participants of the seminar were  Mr. Rajeev Shukla ,Deputy Director General , AIR, Dr R Sreedher, Expert Community Radio, Ms Shrinkhala Sahai, Content Manager and RJ, Ms. Akriti Jakmola, RJ Nasha and Mr Rahul Makin , RJ, Fever 104. The event was attended by media students from Jims Vasant Kunj and Jims Lajpat Nagar  fraternity.