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What are the benefits of Apache Pig over MapReduce?

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What are the benefits of Apache Pig over MapReduce?

a. Advantages of Apache Pig

  • Less development time.
  • Easy to learn.
  • Procedural language.
  • Dataflow.
  • Easy to control execution.
  • UDFs.
  • Lazy evaluation.
  • Usage of Hadoop features.

What is the difference between Pig and SQL?

Apache Pig Vs SQL Pig Latin is a procedural language. SQL is a declarative language. In Apache Pig, schema is optional. We can store data without designing a schema (values are stored as $01, $02 etc.)

What is the difference between hive and MapReduce?

Provide SQL type language which is called HQL. Helps in querying large data sets stored in HDFS(Hadoop Distributed File System). It is an open-source tool….MapReduce vs Hive.

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S.No MapReduce Hive
2. It converts the job into map-reduce functions. It converts the SQL queries to HQL(Hive-QL)

What is difference between Pig Latin and SQL?

The most significant difference is that Pig Latin is a data flow programming language, whereas SQL is a declarative programming language. In other words, a Pig Latin program is a step-by-step set of operations on an input relation, in which each step is a single transformation.

What is the relationship between MapReduce and Pig?

Hadoop MapReduce is a compiled language whereas Apache Pig is a scripting language and Hive is a SQL like query language. Pig and Hive provide higher level of abstraction whereas Hadoop MapReduce provides low level of abstraction. Hadoop MapReduce requires more lines of code when compared to Pig and Hive.

Does Pig differ from MapReduce if yes how?

Yes, Pig differs from MapReduce because, in MapReduce, the group by operation is performed at reducer side and filter, and also in the map phase the projection is implemented. Pig Latin provides the operations that are similar to MapReduce, such as groupby, orderby, and filters.

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Why Pig is data flow language?

Pig–Pig is a data-flow language for expressing Map/Reduce programs for analyzing large HDFS distributed datasets. Pig provides relational (SQL) operators such as JOIN, Group By, etc. Pig is also having easy to plug in Java functions. Cascading pipe and filter processing model.

What are the features of Pig?

The Features of Apache Pig are as follows,

  • Rich set of operators. Apache pig has a rich collection set of operators in order to perform operations like join, filer, and sort.
  • Ease of Programming.
  • Optimization opportunities.
  • Extensibility.
  • User Define Functions (UDF’s)
  • Handles all types of data.
  • ETL (Extract Transform Load)

Is Pig a data warehouse?

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, clickstreams, and search logs.

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What are the different data types in Pig Latin?

Pig Latin has these four types in its data model:

  • Atom: An atom is any single value, such as a string or a number — ‘Diego’, for example.
  • Tuple: A tuple is a record that consists of a sequence of fields.
  • Bag: A bag is a collection of non-unique tuples.
  • Map: A map is a collection of key value pairs.

Which of the following statement most accurately describe the relationship between MapReduce and Pig?

Which of the following statements most accurately describes the relationship between MapReduce and Pig? MapReduce jobs via the Pig interpreter. Pig programs rely on MapReduce but are extensible, allowing developers to do special-purpose. processing not provided by MapReduce.

What is the relationship between Pig and MapReduce?