Hive provides a data warehouse environment in Hadoop with a SQL-like wrapper and also translates the SQL commands in MapReduce jobs for processing. SQL commands in Hive are called as HiveQL, which doesn't support the SQL 92 dialect and should not be assumed to support all the keywords, as the whole idea is to hide the complexity of MapReduce programming and perform analysis on the data.
Hive can also act as an analytical interface with other systems as most of the systems integrate well with Hive. Hive cannot be used for handling transactions, as it doesn't provide row-level updates and real-time queries.
Hive architecture has different components such as:
Driver: Driver manages the lifecycle of a HiveQL statement as it moves through Hive and also maintains a session handle for session statistics.
Metastore: Metastore stores the system catalog and metadata about tables, columns, partitions, and so on.
Query Compiler: It compiles HiveQL into a DAG of optimized map...
