Database Reference
In-Depth Information
X234823904 2013-11-04 12:53:19 34567678 Mary Jones
mary.jones@isp.com
The use of joins and SQL in general will be covered in Chapter 11. To exit the Hive
interactive environment, use quit .
hive> quit;
$
An alternative to running in the interactive environment is to collect the HiveQL
statements in a script (for example, my_script.sql ) and then execute the file as
follows:
$ hive -f my_script.sql
This introduction to Hive provided some of the basic HiveQL commands and
statements. The reader is encouraged to research and utilize, when appropriate,
other Hive functionality such as external tables, explain plans, partitions, and the
INSERT INTO command to append data to the existing content of a Hive table.
Following are some Hive use cases:
Exploratory or ad-hoc analysis of HDFS data: Data can be queried,
transformed, and exported to analytical tools, such as R.
Extracts or data feeds to reporting systems, dashboards, or data
repositories such as HBase: Hive queries can be scheduled to provide
such periodic feeds.
Combining external structured data to data already residing in
HDFS: Hadoop is excellent for processing unstructured data, but often
there is structured data residing in an RDBMS, such as Oracle or SQL
Server, that needs to be joined with the data residing in HDFS. The data
from an RDBMS can be periodically added to Hive tables for querying
with existing data in HDFS.
10.2.3 HBase
Unlike Pig and Hive, which are intended for batch applications, Apache HBase
is capable of providing real-time read and write access to datasets with billions
of rows and millions of columns. To illustrate the differences between HBase
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