Red Hat

Red Hat Linux 5 - Installation

Red Hat Linux 5 - Installation

Step 1 – Insert the Red Hat Linux DVD into the DVD-drive of your computer. As soon as the following screen pops up, press ‘Enter’ to install Red Hat Enterprise Linux (RHEL) through GUI mode.

Step 2– RHEL installer would then prompt you conduct a check as to whether the CD media from which you’re installing is functioning correctly or not. Choose ‘Skip’, press enter and the installation would begin.

Step 3– Next, we need to select the language- English or any other language as per your preference, and then press ‘Next’ .

Step 4– In this step, the RHEL installer would ask you about the appropriate type of keyboard for the system. We take the ‘US English’ keyboard, you can pick any other option depending on the type of your keyboard. Then press ‘Next’ to move to the next step.

Step 5– Next, the installer would ask for an ‘installation number’ if you wish to install full set of Red Hat functionalities. Enter the installation number and press ‘OK’ if you have an officially licensed installation number(for corporate clients that buy Red Hat’s backup support and full features).

Others can select ‘Skip entering installation number’ and press ‘OK’ to proceed. RHEL would show a warning message, press ‘Skip’ in it to continue.

Step 6– The Red Hat installer would then require you to create partitions in your computer’s hard disk for the installation. You can do it in four ways but the simplest way is to select ‘Use free space on selected drives and create default layout’ as this option will not affect any other OS residing in your system.

Check the ‘review and modify portioning layout’ to create partitions and click next.

Step 7– In this step you must create the required system partitions and mount points such as ‘/boot’, ‘/home’, ‘swap’ etc which are required for the Linux’s proper functioning.

To create different partitions such as /home, /var etc, click on ‘New’ to create the partitions.

Then, select /home in the mount point and choose ‘ext3’ as the file system and give the desired size for it and then click ‘OK’. Similarly also create /boot and /var.

Also, create a swap partition by clicking on ‘New’ and then choosing the filesystem as ‘swap’ and also give the size of Swap partition.(Usually size of swap partition SHOULD BE twice the size of RAM available to the system but you can keep its size less than that too)

Once you have made all the desired partitions and given their mount points, click ‘Next’ to continue installation.

Step 8– This step pertains to the default OS that will be loaded by the GRUB loader

(Note- If you have multiple Operating Systems installed, you would see multiple options here and you have to check in front of the OS name that you want to be loaded by default when the system is started.)

Click ‘Next’ to continue.

Step 9– This step pertains to the network settings of the Linux system that you are going to install. You can select the Ethernet devices through which the system would communicate with other devices in the network.

You can also provide the hostname, Gateway address and DNS address to the system during this step. (However it’s better to adjust these settings once the system has been fully installed).

Step 10– The next step is to adjust the system clock to your particular time zone. Select your time zone and then click ‘Next’.

Step 11 – This is a very important step that deals with the root(super-user) password for the system . Type the password and confirm it and then click next.

Step 12 – The RHEL installer would then prompt you about if you wish to install some extra ‘Software Development’ or ‘Web Server’ features. By default, keep it at ‘Customize later’ and press ‘Next’.

 Step 13– This next step will initiate the installation of Red Hat Linux, press ‘Next’ to begin the process.

Step 14– Upon the completion of installation you should the following screen. Press Reboot and you’d be ready to use your newly installed Red Hat Linux OS.

POST INSTALLATION CONFIGURATIONS

1. Accept the Red Hat License agreement and click ‘Forward.

2. The next step is regarding the configuration of the Firewall. You can Enable or Disable the firewall according to your preferences and then click ‘Forward’.

3. Next step is about the configuration of another security tool- SE Linux. By default you should keep it ‘Disabled’ unless you’re working with very secure information.

4. You can also choose to configure the Kdump, that stores information about system crashes if your system fails but uses valuable disk space. By default don’t enable it.

5. Next, adjust the time and date settings, and then click ‘Forward’.

6. The next step is for software updates from Red Hat, at this point you should skip the registration and register at a later time and then click ‘Forward’.

7. This step is to create a non-admin user for the system. Enter the details and click ‘Forward’.

8. This step is about configuration of your Sound Card, choose a sound device and then click ‘Forward’.

9. Click ‘Forward’ to complete the configurations and start using your Red Hat Linux OS.

(Note- On clicking ‘Finish’ the system would require a reboot if you have made changes to the configurations of Firewall or SE Linux.)

Your Red Hat Linux OS is now all installed and configured, ready to be used. Good luck using and exploring various features of Red Hat Linux.

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Oracle Tech Article – Taking Your OBIEE to the Next Level with SmartView VBA 11.1.1.7.1

Oracle Tech Article – Taking Your OBIEE to the Next Level 

with SmartView VBA 11.1.1.7.1

       A data warehouse is the main repository of the organization's historical data, its corporate memory. For example, an organization would use the information that's stored in its data warehouse to find out what day of the week they sold the most widgets in May 1992, or how employee sick leave the week before the winter break differed between California and New York from 2001-2005. In other words, the data warehouse contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis on the information without slowing down the operational systems.

     While operational systems are optimized for simplicity and speed of modification (online transaction processing, or OLTP) through heavy use of database normalization and an entity-relationship model, the data warehouse is optimized for reporting and analysis (on line analytical processing, or OLAP). Frequently data in data warehouses is heavily denormalised, summarised and/or stored in a dimension-based model but this is not always required to achieve acceptable query response times.

More formally, Bill Inmon (one of the earliest and most influential practitioners) defined a data warehouse as follows:

Subject-oriented, meaning that the data in the database is organized so that all the data elements relating to the same real-world event or object are linked together;

Time-variant, meaning that the changes to the data in the database are tracked and recorded so that reports can be produced showing changes over time; obieefans.com

Non-volatile, meaning that data in the database is never over-written or deleted, once committed, the data is static, read-only, but retained for future reporting;

Integrated, meaning that the database contains data from most or all of an organization's operational applications, and that this data is made consistent  History of data warehousing

Data Warehouses became a distinct type of computer database during the late 1980s and early 1990s. They were developed to meet a growing demand for management information and analysis that could not be met by operational systems. Operational systems were unable to meet this need for a range of reasons:

·         The processing load of reporting reduced the response time of the operational systems,

·         The database designs of operational systems were not optimized for information analysis and reporting,

·         Most organizations had more than one operational system, so company-wide reporting could not be supported from a single system, and

·         Development of reports in operational systems often required writing specific computer programs which was slow and expensive.

As a result, separate computer databases began to be built that were specifically designed to support management information and analysis purposes. These data warehouses were able to bring in dat

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Oracle

Oracle Database Architecture

An Oracle database is a collection of data treated as a unit. The purpose of a database is to store and retrieve related information. A database server is the key to solving the problems of information management. In general, a server reliably manages a large amount of data in a multiuser environment so that many users can concurrently access the same data. All this is accomplished while delivering high performance. A database server also prevents unauthorized access and provides efficient solutions for failure recovery.
Oracle Database is the first database designed for enterprise grid computing, the most flexible and cost effective way to manage information and applications. Enterprise grid computing creates large pools of industry-standard, modular storage and servers. With this architecture, each new system can be rapidly provisioned from the pool of components. There is no need for peak workloads, because capacity can be easily added or reallocated from the resource pools as needed.
The database has logical structures and physical structures. Because the physical and logical structures are separate, the physical storage of data can be managed without affecting the access to logical storage structures.
The section contains the following topics:

• Overview of Oracle Grid Architecture
• Overview of Application Architecture
• Overview of Physical Database Structures
• Overview of Logical Database Structures
• Overview of Schemas and Common Schema Objects
• Overview of the Oracle Data Dictionary
• Overview of the Oracle Instance
• Overview of Accessing the Database
• Overview of Oracle Utilities

Overview of Oracle Grid Architecture

Grid computing is a new IT architecture that produces more resilient and lower cost enterprise information systems. With grid computing, groups of independent, modular hardware and software components can be connected and rejoined on demand to meet the changing needs of businesses.
The grid style of computing aims to solve some common problems with enterprise IT: the problem of application silos that lead to under utilized, dedicated hardware resources, the problem of monolithic, unwieldy systems that are expensive to maintain and difficult to change, and the problem of fragmented and disintegrated information that cannot be fully exploited by the enterprise as a whole.
Benefits of Grid Computing Compared to other models of computing, IT systems designed and implemented in the grid style deliver higher quality of service, lower cost, and greater flexibility. Higher quality of service results from having no single point of failure, a robust security infrastructure, and centralized, policy-driven management. Lower costs derive from increasing the utilization of resources and dramatically reducing management and maintenance costs. Rather than dedicating a stack of software and hardware to a specific task, all resources are pooled and allocated on demand, thus eliminating under utilized capacity and redundant capabilities. Grid computing also enables the use of smaller individual hardware components, thus reducing the cost of each individual component and providing more flexibility to devote resources in accordance with changing needs.

Grid Computing Defined

The grid style of computing treats collections of similar IT resources holistically as a single pool, while exploiting the distinct nature of individual resources within the pool. To address simultaneously the problems of monolithic systems and fragmented resources, grid computing achieves a balance between the benefits of holistic resource management and flexible independent resource control. IT resources managed in a grid include:

• Infrastructure: the hardware and software that create a data storage and program execution environment
  
• Applications: the program logic and flow that define specific business processes
  
• Information: the meanings inherent in all different types of data used to conduct business
  

Core Tenets of Grid Computing Two core tenets uniquely distinguish grid computing from other styles of computing, such as mainframe, client-server, or multi-tier: virtualization and provisioning.

• With virtualization, individual resources (e.g. computers, disks, application components and information sources) are pooled together by type then made available to consumers (e.g. people or software programs) through an abstraction. Virtualization means breaking hard-coded connections between providers and consumers of resources, and preparing a resource to serve a particular need without the consumer caring how that is accomplished.
  
• With provisioning, when consumers request resources through a virtualization layer, behind the scenes a specific resource is identified to fulfill the request and then it is allocated to the consumer. Provisioning as part of grid computing means that the system determines how to meet the specific need of the consumer, while optimizing operation of the system as a whole.
  The specific ways in which information, application or infrastructure resources are virtualized and provisioned are specific to the type of resource, but the concepts apply universally. Similarly, the specific benefits derived from grid computing are particular to each type of resource, but all share the characteristics of better quality, lower costs and increased flexibility.
  

Infrastructure Grid Infrastructure grid resources include hardware resources such as storage, processors, memory, and networks as well as software designed to manage this hardware, such as databases, storage management, system management, application servers, and operating systems.
Virtualization and provisioning of infrastructure resources mean pooling resources together and allocating to the appropriate consumers based on policies. For example, one policy might be to dedicate enough processing power to a web server that it can always provide sub-second response time. That rule could be fulfilled in different ways by the provisioning software in order to balance the requests of all consumers.
Treating infrastructure resources as a single pool and allocating those resources on demand saves money by eliminating under utilized capacity and redundant capabilities. Managing hardware and software resources holistically reduces the cost of labor and the opportunity for human error.
Spreading computing capacity among many different computers and spreading storage capacity across multiple disks and disk groups removes single points of failure so that if any individual component fails, the system as a whole remains available. Furthermore, grid computing affords the option to use smaller individual hardware components, such as blade servers and low cost storage, which enables incremental scaling and reduces the cost of each individual component, thereby giving companies more flexibility and lower cost.
Infrastructure is the dimension of grid computing that is most familiar and easy to understand, but the same concepts apply to applications and information.
Applications Grid

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Mongo DB

MongoDB is a cross-platform, document oriented database that provides, high performance, high availability, and easy scalability. MongoDB works on concept of collection and document.

Database

Database is a physical container for collections. Each database gets its own set of files on the file system. A single MongoDB server typically has multiple databases.

Collection

Collection is a group of MongoDB documents. It is the equivalent of an RDBMS table. A collection exists within a single database. Collections do not enforce a schema. Documents within a collection can have different fields. Typically, all documents in a collection are of similar or related purpose.

Document

A document is a set of key-value pairs. Documents have dynamic schema. Dynamic schema means that documents in the same collection do not need to have the same set of fields or structure, and common fields in a collection's documents may hold different types of data.
Below given table shows the relationship of RDBMS terminology with MongoDB

RDBMS	MongoDB
Database	Database
Table	Collection
Tuple/Row	Document
column	Field
Table Join	Embedded Documents
Primary Key	Primary Key (Default key _id provided by mongodb itself)
Database Server and Client
Mysqld/Oracle	mongod
mysql/sqlplus	mongo

Sample document

Below given example shows the document structure of a blog site which is simply a comma separated key value pair.

{
   _id: ObjectId(7df78ad8902c)
   title: 'MongoDB Overview', 
   description: 'MongoDB is no sql database',
   by: 'tutorials point',
   url: 'http://www.tutorialspoint.com',
   tags: ['mongodb', 'database', 'NoSQL'],
   likes: 100, 
   comments: [ 
      {
         user:'user1',
         message: 'My first comment',
         dateCreated: new Date(2011,1,20,2,15),
         like: 0 
      },
      {
         user:'user2',
         message: 'My second comments',
         dateCreated: new Date(2011,1,25,7,45),
         like: 5
      }
   ]
}

_id is a 12 bytes hexadecimal number which assures the uniqueness of every document. You can provide _id while inserting the document. If you didn't provide then MongoDB provide a unique id for every document. These 12 bytes first 4 bytes for the current timestamp, next 3 bytes for machine id, next 2 bytes for process id of mongodb server and remaining 3 bytes are simple incremental value.

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