为什么使用Hive

Hive is a data warehouse software that facilitates reading, writing, and managing large data sets stored in the Hadoop file system. Hive is designed to enable easy data summarization, ad-hoc querying, and analysis of large data sets.

Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time, this flexibility enables programmers to be able to extend the capabilities of HiveQL with their own custom functions (UDFs).

Hive is not designed for online transaction processing (OLTP) and does not provide row-level insert, update, and delete. It is better suited for batch jobs over large sets of append-only data (such as web logs).

The key reasons to use Hive are:

1.

Hive supports ACID (atomicity, consistency, isolation, durability) transactions. This is a major advantage over other Hadoop-based solutions, which only support eventual consistency.

2.

Hive has a well-defined SQL-like query language, called HiveQL, which is similar to the languages used by traditional relational database systems. This makes it much easier for developers and analysts who are familiar with SQL to get started with Hive.

3.

Hive supports a wide variety of data formats, including popular formats such as JSON, XML, and Avro. This makes it easy to integrate Hive with existing data sources.

4.

Hive comes with a built-in metastore, which makes it easy to manage and share Hive tables and partitions across different teams and projects.

5.

Hive supports a number of features that make it suitable for large-scale data processing, including partitioning, bucketing, and windowing.