Hive is a data warehouse infrastructure built on top of Hadoop, designed to facilitate querying and managing large datasets residing in distributed storage using SQL-like syntax. It translates SQL queries into MapReduce jobs, enabling efficient data analysis and summarization.
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About Hive
Hive was created in 2008 by Facebook to address the challenge of managing and querying large datasets stored in Hadoop. It aimed to make data processing more accessible to analysts by providing an SQL-like interface, which simplified the interaction with Hadoop's complex MapReduce framework.
Hive's strengths include its ability to handle large datasets, SQL-like interface, and seamless integration with Hadoop. Its weaknesses are slower query performance compared to some modern data processing tools and higher latency due to reliance on MapReduce. Competitors include Apache Spark, Presto, and Google BigQuery.
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How to hire a Hive expert
A Hive expert must have strong proficiency in SQL, deep understanding of Hadoop and HDFS, experience with MapReduce, knowledge of data warehousing concepts, and familiarity with scripting languages like Python or Java for custom UDFs.
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