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HiveQL
TLDR: HiveQL (Hive Query Language), introduced in 2010 as part of Apache Hive, is a powerful query language designed for querying and analyzing large-scale data stored in distributed environments such as Hadoop Distributed File System (HDFS). It features syntax similar to SQL, enabling users to perform operations like joins, aggregations, and filtering on structured and semi-structured data types. HiveQL simplifies complex big data workflows and is widely adopted for batch processing and advanced data analytics.
HiveQL integrates seamlessly with the Hadoop Ecosystem, allowing users to interact with tools like Apache Spark and Apache HBase for hybrid processing. It supports custom user-defined functions (UDFs) and works well with a variety of programming terms such as Java, Python, and Scala. With its ability to handle massive datasets in hybrid and cloud database environments, HiveQL is widely used in industries like finance, telecommunications, and retail for large-scale analytics and data science applications.
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