Advanced Oracle PL/SQL Developer's Guide - Second Edition by Gupta Saurabh K
Author:Gupta, Saurabh K. [Gupta, Saurabh K.]
Language: eng
Format: azw3
Publisher: Packt Publishing
Published: 2016-02-15T05:00:00+00:00
Oracle SecureFilesAn overview
Working with Securefiles
Migrating BasicFiles to SecureFiles
Oracle Database 12c SecureFiles enhancements
Introduction to Large Objects
As the name suggests, large objects or LOBs refer to large data. A column of a large object type in a table can store semi-structured or unstructured data. Semi-structured data can be a character-based document that can be processed in a near relational format. Unstructured data is a binary file that is difficult to interpret logically. For example, an XML file is a semi-structured document while an image or a graphics file is an unstructured format of the data.
Oracle Database supports the storage of large objects along the following aspects:
Storage: Just like any other data, the Oracle Database allows the storage of large objects in columns within a table. The columns of LOB data types can efficiently store a semi or unstructured data object, compress it and even encrypt it in the database. The LOB datatype stored in the Oracle Database abides by the ACID (Atomicity, Consistency, Isolation, and Durability) properties. Oracle provides a wide range of administrative controls to manage and maintain large objects in the database.
Access: Oracle SecureFiles (discussed later in this chapter) provides you with highly optimized access of large objects from the Oracle Database. SecureFiles, introduced in Oracle Database 11g and the default LOB storage option in Oracle Database 12c, accelerates LOB performance through vector optimization techniques. For semi-structured data types such as Oracle Text or Oracle Spatial, Oracle enables indexing techniques to improve query performance.
Security: The LOB data type in the Oracle Database stays protected and secure. Fine-grained data access security policies apply to large objects as well.
Download
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.
Algorithms of the Intelligent Web by Haralambos Marmanis;Dmitry Babenko(8295)
Azure Data and AI Architect Handbook by Olivier Mertens & Breght Van Baelen(6700)
Building Statistical Models in Python by Huy Hoang Nguyen & Paul N Adams & Stuart J Miller(6676)
Serverless Machine Learning with Amazon Redshift ML by Debu Panda & Phil Bates & Bhanu Pittampally & Sumeet Joshi(6548)
Data Wrangling on AWS by Navnit Shukla | Sankar M | Sam Palani(6337)
Driving Data Quality with Data Contracts by Andrew Jones(6284)
Machine Learning Model Serving Patterns and Best Practices by Md Johirul Islam(6053)
Learning SQL by Alan Beaulieu(5994)
Weapons of Math Destruction by Cathy O'Neil(5778)
Big Data Analysis with Python by Ivan Marin(5345)
Data Engineering with dbt by Roberto Zagni(4344)
Solidity Programming Essentials by Ritesh Modi(3990)
Time Series Analysis with Python Cookbook by Tarek A. Atwan(3848)
Pandas Cookbook by Theodore Petrou(3556)
Blockchain Basics by Daniel Drescher(3292)
Hands-On Machine Learning for Algorithmic Trading by Stefan Jansen(2904)
Feature Store for Machine Learning by Jayanth Kumar M J(2808)
Learn T-SQL Querying by Pam Lahoud & Pedro Lopes(2791)
Mastering Python for Finance by Unknown(2743)
