Apache Pig Vs MapReduce
Listed below are the major differences between Apache Pig and MapReduce.
| Apache Pig | MapReduce |
|---|---|
| Apache Pig is a data flow language. | MapReduce is a data processing paradigm. |
| It is a high level language. | MapReduce is low level and rigid. |
| Performing a Join operation in Apache Pig is pretty simple. | It is quite difficult in MapReduce to perform a Join operation between datasets. |
| Any novice programmer with a basic knowledge of SQL can work conveniently with Apache Pig. | Exposure to Java is must to work with MapReduce. |
| Apache Pig uses multi-query approach, thereby reducing the length of the codes to a great extent. | MapReduce will require almost 20 times more the number of lines to perform the same task. |
| There is no need for compilation. On execution, every Apache Pig operator is converted internally into a MapReduce job. | MapReduce jobs have a long compilation process. |
Apache Pig Vs SQL
Listed below are the major differences between Apache Pig and SQL.
| Pig | SQL |
|---|---|
| Pig Latin is aprocedurallanguage. | SQL is adeclarativelanguage. |
| In Apache Pig,schemais optional. We can store data without designing a schema (values are stored as $01, $02 etc.) | Schema is mandatory in SQL. |
| The data model in Apache Pig isnested relational. | The data model used in SQLis flat relational. |
| Apache Pig provides limited opportunity forQuery optimization. | There is more opportunity for query optimization in SQL. |