pig hive sqoop flume - Wikitechy

What is the difference between sqoop and pig ?

Editor — Thu, 22 Jul 2021 06:59:29 +0000

Pig is a platform for managing large data.
It uses high level programming to analyse the data.
The programming is done using the language pig latin.
It is simple and highly specific.
The pig Metastore stores all info about the tables. And we can execute spark sql queries because spark can interact with pig Metastore

Sqoop is a simple tool used for transferring large amount of data.
It is used for transferring data from hadoop to relational database.
sqoop can import data from Oracle,MYSQL,SQl.
Sqoop metastore is a tool for using hosts in a shared metadata repository. Multiple users and remote users execute saved jobs in metastore.

Editor — Mon, 12 Jul 2021 08:36:31 +0000

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.

Editor — Mon, 12 Jul 2021 05:12:12 +0000

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.