- What are the advantages of hive?
- Is hive similar to SQL?
- Is Hadoop a database?
- How does hive work in Hadoop?
- Can hive run without Hadoop?
- Is hive an ETL tool?
- Which is better Hive or Pig?
- Can hive be used for unstructured data?
- Is Hadoop OLTP or OLAP?
- Does Facebook use hive?
- What is difference between Hadoop and HDFS?
- What are the features of hive?
- What is the purpose of hive in Hadoop?
- What is the difference between Hive and Hadoop?
- How is data stored in hive?
What are the advantages of hive?
Advantages of HiveKeeps queries running fast.Takes very less time to write Hive query in comparison to MapReduce code.HiveQL is a declarative language like SQL.Provides the structure on an array of data formats.Multiple users can query the data with the help of HiveQL.Very easy to write query including joins in Hive.More items…•.
Is hive similar to SQL?
HiveQL is a query language for Hive to analyze and process structured data in a Meta-store. It is very much similar to SQL and highly scalable. It reuses familiar concepts from the relational database world, such as tables, rows, columns and schema, to ease learning.
Is Hadoop a database?
Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers.
How does hive work in Hadoop?
How Does Apache Hive Work? In short, Apache Hive translates the input program written in the HiveQL (SQL-like) language to one or more Java MapReduce, Tez, or Spark jobs. … Apache Hive then organizes the data into tables for the Hadoop Distributed File System HDFS) and runs the jobs on a cluster to produce an answer.
Can hive run without Hadoop?
Hadoop is like a core, and Hive need some library from it. Update This answer is out-of-date : with Hive on Spark it is no longer necessary to have hdfs support. Hive requires hdfs and map/reduce so you will need them. … But the gist of it is: hive needs hadoop and m/r so in some degree you will need to deal with it.
Is hive an ETL tool?
Extract, Transform, and Load (ETL) operations are used to prepare data and load it into a data destination. Apache Hive on HDInsight can read in unstructured data, process the data as needed, and then load the data into a relational data warehouse for decision support systems.
Which is better Hive or Pig?
Pig vs. Apache Pig is 10% faster than Apache Hive for filtering 10% of the data. Apache Pig is 18% faster than Apache Hive for filtering 90% of the data.
Can hive be used for unstructured data?
Yes. It can be processed. What needs to be done is transform unstructured data to structured form. One approach can be like develop ETL(Spark/pig/Map reduce) pipeline which will extract required data elements/columns from the unstructured data and load into hive HIVE table.
Is Hadoop OLTP or OLAP?
OLTP is said to be more of an online transactional system or data storage system, where the user does lots of online transactions using the data store. … Cassandra is said to be more of OLTP, as it is real-time, whereas Hadoop is more of OLAP, since it is used for analytics and bulk writes.
Does Facebook use hive?
Hive is an open source, peta-byte scale date warehousing framework based on Hadoop that was developed by the Data Infrastructure Team at Facebook. … Apart from ad hoc analysis and business intelligence applications used by analysts across the company, a number of Facebook products are also based on analytics.
What is difference between Hadoop and HDFS?
HDFS is a Java based distributed file system that allows you to store large data across multiple nodes in a Hadoop cluster. Whereas HBase is a NoSQL database (similar as NTFS and MySQL). … HBase supports random read and writes while HDFS supports WORM (Write once Read Many or Multiple times).
What are the features of hive?
Features of HiveIt stores schema in a database and processed data into HDFS.It is designed for OLAP.It provides SQL type language for querying called HiveQL or HQL.It is familiar, fast, scalable, and extensible.
What is the purpose of hive in Hadoop?
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.
What is the difference between Hive and Hadoop?
Hadoop: Hadoop is a Framework or Software which was invented to manage huge data or Big Data. Hadoop is used for storing and processing large data distributed across a cluster of commodity servers. Hive is an SQL Based tool that builds over Hadoop to process the data. …
How is data stored in hive?
Hive data are stored in one of Hadoop compatible filesystem: S3, HDFS or other compatible filesystem. Hive metadata are stored in RDBMS like MySQL, see supported RDBMS. The location of Hive tables data in S3 or HDFS can be specified for both managed and external tables.