|#Top Apache HIVE excellent built-in features for Big data:|
It delivers an SQL-like lingo named when keeping complete aid aimed at map/reduce. To accelerate requests, it delivers guides, containing bitmap guides.
By preset, Hive stores metadata in an implanted Apache Derby database, and different client/server databases like MySQL may optionally be applied.
Currently, there are 4 file setups maintained in Hive, that are TEXTFILE, SEQUENCE FILE, ORC and RCFILE.
Other attributes of Hive include:
- Indexing to supply quickening, directory sort containing compacting and Bitmap directory as of 0.10, further directory kinds are designed.
- Different depository kinds such like simple written material, RCFile, HBase, ORC, and other ones.
- Metadata depository in an RDBMS, notably decreasing the time to accomplish verbal examines throughout request implementation.
- Operating on compressed information kept in to Hadoop environment, set of rules containing gzip, bzip2, snappy, etcetera.
- Built-in exploiter described purposes (UDFs) to manipulate dates, cords, and different data-mining implements. Hive aids expanding the UDF set to cover use-cases not maintained by integrated purposes.
- SQL-like requests (Hive QL), that are completely changed in to map-reduce appointments.