HIVE
Hive is a data warehouse infrastructure that provides data summarization and ad-hoc querying. Hive provides an SQL dialect, called Hive Query Language (abbreviated HQL) for querying data stored in a Hadoop cluster.
Hive’s data model provides a high-level, table-like structure on top of HDFS. It supports three data structures:
tables, partitions, and buckets, where tables correspond to HDFS
directories and can be divided into partitions, which in turn can be divided into buckets.
Hive supports a majority of primitive data formats such as TINYINT, TIMESTAMP, STRING, FLOAT, BOOLEAN, DECIMAL, DOUBLE, INT, SMALLINT, BIGINT, and
complex data types, such as UNION, STRUCT, MAP, and ARRAY.
Hive User Interface consists of the CLI(command line interface), a web interface called Hive web interface (HWI), and programmatic access through JDBC, ODBC, and a Thrift server.
All commands and queries goes to the Driver, which compiles the input, optimizes the computation required, and executes the required steps, usually with MapReduce jobs. Execution Engine can be MapReduce,Tez or Spark.
The Metastore is a separate relational database where Hive persists table schemas and other system metadata.
To start the hive shell:-
Hive’s data model provides a high-level, table-like structure on top of HDFS. It supports three data structures:
tables, partitions, and buckets, where tables correspond to HDFS
directories and can be divided into partitions, which in turn can be divided into buckets.
Hive supports a majority of primitive data formats such as TINYINT, TIMESTAMP, STRING, FLOAT, BOOLEAN, DECIMAL, DOUBLE, INT, SMALLINT, BIGINT, and
complex data types, such as UNION, STRUCT, MAP, and ARRAY.
Hive Architecture
All commands and queries goes to the Driver, which compiles the input, optimizes the computation required, and executes the required steps, usually with MapReduce jobs. Execution Engine can be MapReduce,Tez or Spark.
The Metastore is a separate relational database where Hive persists table schemas and other system metadata.
To start the hive shell:-
[hduser@localhost ~]$ cd $HIVE_HOME
[hduser@localhost hive]$ cd bin
[hduser@localhost bin]$ pwd
/usr/local/hadoop/hive/bin
[hduser@localhost bin]$ hive
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.6.0/hive/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.6.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Logging initialized using configuration in jar:file:/usr/local/hadoop-2.6.0/hive/lib/hive-common-2.1.0.jar!/hive-log4j2.properties Async: true
Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
hive>
Hi
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