HiveQL
HiveQL is a SQL-like query language used in Apache Hive, a data warehouse infrastructure built on top of Hadoop for data summarization, querying, and analysis. It allows developers and data analysts to write SQL-style queries to process and analyze large datasets stored in Hadoop Distributed File System (HDFS) or other compatible storage systems. HiveQL translates queries into MapReduce, Tez, or Spark jobs, enabling scalable big data processing without requiring deep knowledge of Java or MapReduce programming.
Developers should learn HiveQL when working with big data ecosystems, especially for batch processing and data warehousing tasks on Hadoop clusters. It is ideal for scenarios involving structured or semi-structured data analysis, such as log processing, business intelligence reporting, and ETL (Extract, Transform, Load) operations, as it simplifies querying large datasets using familiar SQL syntax. Use cases include data aggregation, filtering, and joining operations on petabytes of data in distributed environments.