Apache Hive is an open source data storage and query tool for analyzing large data sets. Hive has been developed as part of the Hadoop ecosystem and can handle data located on the Hadoop Distributed File System (HDFS). Since Hive has a SQL-like query language, even data analysts who do not know SQL can easily query large data sets using Hive.
Hive allows users to run their queries on Hadoop. These queries are run in parallel with the MapReduce engine. It is also possible to query, filter, aggregate and group data using a SQL-like query language called HiveQL. Hive can also be integrated with tools such as ODBC and JDBC that can connect to many data sources.
Loading data into Hive tables is pretty easy. CSV or other file formats can be used and data is loaded directly into Hive tables. In addition, Hive can be integrated with charting tools to visualize summary statistics, patterns and trends of data.
Hive offers many advantages for large datasets. One of them is the high-performance processing of data. In addition, Hive is a low-cost solution for storing, processing and querying large data sets. Increasing use of Hive in data analytics can help businesses make more efficient and smarter decisions.
All in all, Data Analysis with Apache Hive is a useful tool for querying and analyzing large datasets. Hive was developed as part of the Hadoop ecosystem and is optimized for working with large datasets. It is also possible to query, filter, aggregate and group data using a SQL-like query language.
https://enessoztrk.medium.com/apachehive-verianalizi-8b50fbc82943