hadoop pig interview questions - Wikitechy https://www.wikitechy.com/interview-questions/tag/hadoop-pig-interview-questions/ Interview Questions Wed, 15 Sep 2021 05:14:15 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 https://www.wikitechy.com/interview-questions/wp-content/uploads/2025/10/cropped-wikitechy-icon-32x32.png hadoop pig interview questions - Wikitechy https://www.wikitechy.com/interview-questions/tag/hadoop-pig-interview-questions/ 32 32 What is the difference between Pig and Sqoop in Hadoop ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-sqoop-in-hadoop/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-sqoop-in-hadoop/#respond Mon, 12 Jul 2021 08:36:31 +0000 https://www.wikitechy.com/interview-questions/?p=209

Difference between Pig and Sqoop in Hadoop

Pig Sqoop
Apache Pig is a tool for analytics which is used to
analyze data stored in HDFS.		 Apache Sqoop is a tool to importing structured data from RDBMS to HDFS or exporting data from HDFS to RDBMS.
We can import the data from Sql databases into
hive rather than NoSql Databases.		 It can integrate with any external data sources with HDFS i.e Sql , NoSql and Data warehouses as well using this tool at the same time we export it as well since this can be used as bi-directional ways
Pig can be used for following purposes ETL
data pipeline, Research on raw data.		 Important Sqoop control commands to import RDBMS data are Append, Columns and Where
The pig Metastore stores all info about the tables.
And we can execute spark sql queries because spark
can interact with pig Metastore.		 Sqoop metastore is a tool for using hosts in a shared metadata repository. Multiple users and remote users can define and execute saved jobs defined in metastore.
The scalar data types in pig are int, float,
double, long, chararray, and bytearray. The complex data
types in Pig are map, tuple, and bag.		 It basically converts CHAR(x), VARCHAR(x), NUMERIC(x,y) to string (with lengh 32767), and it converts DATETIME to BIGINT.
]]> https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-sqoop-in-hadoop/feed/ 0 What is the difference between Pig and Hive ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-hive/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-hive/#respond Mon, 12 Jul 2021 08:22:29 +0000 https://www.wikitechy.com/interview-questions/?p=205

Difference between pig and Hive

Pig Hive
Pig Hadoop Component is generally
used by Researchers and Programmers.		 Hive Hadoop Component is mainly used by data analysts.
Pig Hadoop Component is used
for semi structured data.		 Hive Hadoop Component is used for completely structured Data.
Pig Hadoop Component has a procedural data
flow language (Pig Latin).		 Hive Hadoop Component has a declarative Structured Query Language (HiveQL).
Pig can’t start reliance based server. Hive can start reliance based server,send queries from any nook and corner directly to the Hive
server which will execute them.
Pig is also SQL like but it varies from great extent
and it will take some time efforts to master Pig.		 Hive directly borrowed SQL expertise it learnt easily.
Avro supported for Pig. Avro does not support for Hive.
Pig Hadoop Component operates on
the client side of any group.		 Hive Hadoop Component operates on the server side of any group.
Pig Hadoop Component is highly
used for programming.		 Hive Hadoop Component is mainly used for generating reports.
Pig Hadoop is a great ETL tool for
big data because of its powerful
transformation and processing capabilities.		 Hive Hadoop Component is helpful for ETL(Extract, Transform and Load).
In Pig there is no dedicated metadata database
and the schemas or data types will
be defined in the script itself.		 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.
Pig Hadoop component does not have
any notion for partitions though might
be one can achieve this through filters.		 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.
Pig Hadoop Component renders users with sample
data for each scenario and each step through
its “Illustrate” function.		 This feature is not incorporated with the
Hive Hadoop Component.
]]> https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-pig-and-hive/feed/ 0 What is the difference between group and cogroup in Pig Latin ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-group-and-cogroup-in-pig-latin/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-group-and-cogroup-in-pig-latin/#respond Mon, 12 Jul 2021 08:13:18 +0000 https://www.wikitechy.com/interview-questions/?p=201

Difference between group and cogroup in Pig Latin

Group Cogroup
For readability GROUP is used
in statements involving one relation		 Cogroup used as a statements involving two or more relations. Cogroup should no exceed 127 relations at a time.
The group statement collects together
records with the same key		 cogroup is a general statement of group. Instead of collecting records of 1 input it collects records of N inputs based on a key
Syntax:
grunt> Group_data = GROUP Relation_name BY age;		 Syntax:
alias = CROSS alias, alias [, alias …] [PARTITION BY partitioner] [PARALLEL n];
]]> https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-difference-between-group-and-cogroup-in-pig-latin/feed/ 0 What is the advantages of pig in Hadoop ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-advantages-of-pig-in-hadoop/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-advantages-of-pig-in-hadoop/#respond Mon, 12 Jul 2021 08:04:01 +0000 https://www.wikitechy.com/interview-questions/?p=197

Advantages of pig in Hadoop

    • The development time is Decrease.
    • It is a collection of Rich set of operators in order to perform operations such as join, filer, sort and many more.
    • Pig Latin is similar to SQL, it becomes very easy for developers to write a Pig script.
    • The task execution in Apache Pig it gets automatically optimized , hence the programmers need to focus on semantics language.
Big data sdd
  • Using the existing operators, users can easily develop their own functions to process,read, and write data.
  • Pig provide the facility for creating User Defined Functions UDF’s, we can easily create a number of programming languages such as Java and invoke them in Pig Scripts.
  • All types of data handling are having both structured & unstructured is provided by Apache Pig and the results are stored inside HDFS.
  • You have UDFs which you want to parallellize and utilize for large amounts of data, then you are in luck. Use Pig as a base pipeline where it does the hard work and you just apply your UDF in the step that you want.
]]> https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-advantages-of-pig-in-hadoop/feed/ 0 What is pig Latin ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-pig-latin/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-pig-latin/#respond Mon, 12 Jul 2021 07:08:15 +0000 https://www.wikitechy.com/interview-questions/?p=190

Pig Latin

  • Pig Latin is not a language but its a language game that all use to speak in code.
  • Altering words in English Pig Latin is formed.
  • Pig Latin can be extended using user-defined functions which the user can write these languages Java, Python, JavaScript, Ruby or Groovy and then call directly.
  • It execute Hadoop jobs in MapReduce, Apache Tez, or Apache Spark
  • Pig Latin abstracts the programming from the Java MapReduce idiom which makes MapReduce programming as a high level, its similar to that SQL for relational database management systems.
Pig Latin
Pig Latin Code
]]> https://www.wikitechy.com/interview-questions/apache-pig/what-is-pig-latin/feed/ 0 What is the history of Pig in Hadoop ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-history-of-pig-in-hadoop/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-the-history-of-pig-in-hadoop/#respond Mon, 12 Jul 2021 05:12:12 +0000 https://www.wikitechy.com/interview-questions/?p=153

History of Pig in Hadoop

  • In 2006 Pig was developed by Yahoo Research for particular way of creating and executing MapReduce jobs on very large data sets.
  • Apache Software Foundation was moved into 2007.
  • Pig started a project in Yahoo! Research, where Yahoo! scientists designed it and produced an implementation.
  • The MapReduce paradigm presented by Hadoop “is too low-level and rigid, and leads to a great deal of custom user code that is hard to maintain and reuse.”
  • Users were not comfortable with MapReduce languages such as SQL.
  • Sort the problem a new language called Pig Latin that we have designed to fit between the declarative style of SQL, and the low-level, procedural style of MapReduce.”
  • Hadoop users adopt Pig. So, a team of development engineers was assembled to take the research prototype and build into a production-quality product. About this same time, in fall 2007, Pig was open sourced via the Apache Incubator.
  • The first Pig release in September 2008, were Pig graduated from the Incubator and became a subproject of Apache Hadoop.
Bigdata history
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