Scalability
Apache Hive is built on top of Hadoop, allowing it to efficiently handle large datasets by distributing the load across a cluster of machines.
SQL-like Interface
Hive provides a familiar SQL-like querying language, HiveQL, which makes it easier for users with SQL knowledge to perform data analysis on large datasets without needing to learn a new syntax.
Integration with Hadoop Ecosystem
Hive integrates seamlessly with other components of the Hadoop ecosystem such as HDFS for storage and MapReduce for processing, making it a versatile tool for big data processing.
Schema on Read
Hive uses a schema-on-read model which allows it to work with flexible data schemas and handle unstructured or semi-structured data efficiently.
Extensibility
Users can extend Hive's capabilities by writing custom UDFs (User Defined Functions), UDAFs (User Defined Aggregate Functions), and SerDes (Serializers/ Deserializers).
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie. Source: about 2 years ago
Hive, A data warehouse infrastructure that provides data summarization and ad hoc querying. - Source: dev.to / over 2 years ago
In this article, I'm showing you how to create a Spring Boot app that loads data from Apache Hive via Apache Spark to the Aerospike Database. More than that, I'm giving you a recipe for writing integration tests for such scenarios that can be run either locally or during the CI pipeline execution. The code examples are taken from this repository. - Source: dev.to / about 3 years ago
ListItem(name='Apache Hive', website='https://hive.apache.org/', category='Interactive Query', short_description='Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.'),. Source: over 3 years ago
Apache Hive takes in a specific SQL dialect and converts it to map-reduce. - Source: dev.to / over 3 years ago
Apache Calcite is a popular parser/optimizer that is used in popular databases and query engines Like Apache Hive, BlazingSQL and many others. - Source: dev.to / over 3 years ago
Both Fortune 500 and small companies are looking for competent people who can derive useful insight from their huge pile of data and that's where Big Data Framework like Apache Hadoop, Apache Spark, Flink, Storm, and Hive can help. - Source: dev.to / about 4 years ago
How to flesh this idea out more? Start ingesting different types of events and putting them in different tables. Definitely try an OLAP solution (Hive? Most of my experience sits with closed source projects that only a company can afford) and think about column optimised file formats. Get the raw data into an OLAP solution and do aggregations into another systems based off of the OLAP solution. Source: about 4 years ago
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