MapReduce是一种在 Hadoop 上工作的模型，可高效访问存储在 HDFS（Hadoop 分布式文件系统）中的大数据。它是 Hadoop 的核心组件，它将大数据分成小块并并行处理。
MapReduce 的特点：
- 它可以在各种服务器上存储和分发大量数据。
- 允许用户将数据存储在地图中并减少表格以进行处理。
- 它保护系统免受任何未经授权的访问。
- 它支持并行处理模型。
Pig是一种基于 Hadoop 生态系统构建的开源工具，用于提供更好的大数据处理。它是一种高级脚本语言，通常称为 Pig Latin 脚本。它适用于支持使用各种类型数据的 HDFS（Hadoop 分布式文件系统）。
猪的特点：
- 它允许用户创建自定义的用户定义函数。
- 它可以扩展使用。
- 支持多种数据类型，例如 char long float 模式和函数。
- 提供对 HDFS 的不同操作，如 GROUP、FILTER、JOIN、SORT。
MapReduce 和 Pig 的区别：
| S.No |
MapReduce |
Pig |
|---|---|---|
| 1. | It is a Data Processing Language. | It is a Data Flow Language. |
| 2. | It converts the job into map-reduce functions. | It converts the query into map-reduce functions. |
| 3. | It is a Low-level Language. | It is a High-level Language |
| 4. | It is difficult for the user to perform join operations. | Makes it easy for the user to perform Join operations. |
| 5. | The user has to write 10 times more lines of code to perform a similar task than Pig. | The user has to write fewer lines of code because it supports the multi-query approach. |
| 6. | It has several jobs therefore execution time is more. | It is less compilation time as the Pig operator converts it into MapReduce jobs. |
| 7. | It is supported by recent versions of the Hadoop. | It is supported with all versions of Hadoop. |