Characteristics of nonlinear data structure

Answer 1

A database is a collection of data organized in a fashion that facilitates updating, retrieving, and managing the data. The data can consist of anything, including, but not limited to names, addresses, pictures, and numbers. Databases are commonplace and are used everyday. For example, an airline reservation system might maintain a database of available flights, customers, and tickets issued. A teacher might maintain a database of student names and grades. Because computers excel at quickly and accurately manipulating, storing, and retrieving data, databases are often maintained electronically using a database management system. Database management systems are essential components of many everyday business operations. Database products like Microsoft SQL Server, Sybase Adaptive Server, IBM DB2, and Oracle serve as a foundation for accounting systems, inventory systems, medical recordkeeping sytems, airline reservation systems, and countless other important aspects of modern businesses. It is not uncommon for a database to contain millions of records requiring many gigabytes of storage. For examples, TELSTRA, an Australian telecommunications company, maintains a customer billing database with 51 billion rows (yes, billion) and 4.2 terabytes of data. In order for a database to be useful and usable, it must support the desired operations, such as retrieval and storage, quickly. Because databases cannot typically be maintained entirely in memory, b-trees are often used to index the data and to provide fast access. For example, searching an unindexed and unsorted database containing n key values will have a worst case running time of O(n); if the same data is indexed with a b-tree, the same search operation will run in O(log n). To perform a search for a single key on a set of one million keys (1,000,000), a linear search will require at most 1,000,000 comparisons. If the same data is indexed with a b-tree of minimum degree 10, 114 comparisons will be required in the worst case. Clearly, indexing large amounts of data can significantly improve search performance. Although other balanced tree structures can be used, a b-tree also optimizes costly disk accesses that are of concern when dealing with large data sets. Databases typically run in multiuser environments where many users can concurrently perform operations on the database. Unfortunately, this common scenario introduces complications. For example, imagine a database storing bank account balances. Now assume that someone attempts to withdraw $40 from an account containing $60. First, the current balance is checked to ensure sufficent funds. After funds are disbursed, the balance of the account is reduced. This approach works flawlessly until concurrent transactions are considered. Suppose that another person simultaneously attempts to withdraw $30 from the same account. At the same time the account balance is checked by the first person, the account balance is also retrieved for the second person. Since neither person is requesting more funds than are currently available, both requests are satisfied for a total of $70. After the first person's transaction, $20 should remain ($60 - $40), so the new balance is recorded as $20. Next, the account balance after the second person's transaction, $30 ($60 - $30), is recorded overwriting the $20 balance. Unfortunately, $70 have been disbursed, but the account balance has only been decreased by $30. Clearly, this behavior is undesirable, and special precautions must be taken. A b-tree suffers from similar problems in a multiuser environment. If two or more processes are manipulating the same tree, it is possible for the tree to become corrupt and result in data loss or errors. The simplest solution is to serialize access to the data structure. In other words, if another process is using the tree, all other processes must wait. Although this is feasible in many cases, it can place an unecessary and costly limit on performance because many operations actually can be performed concurrently without risk. Locking, introduced by Gray and refined by many others, provides a mechanism for controlling concurrent operations on data structures in order to prevent undesirable side effects and to ensure consistency. For a detailed discussion of this and other concurrency control mechanisms, please refer to the references below. reference http://www.bluerwhite.org/btree/

Answer 2

The same change in the independent variable brings about different changes in the dependent variable according to the value of the independent variable.

What I am trying to say formally in that tongue-twister (or mind-twister) is that if x and y are two variables (x independent), then the differerence between the y values when x is 1 and when x is 2 (change in x = 1) is not the same as the difference between the y values when x is 5 and when x is 6 (again, change in x = 1). They depend on x being near 1 or near 5.

Answer 3

see array is linear on it requires continues memory locations. the data structures like linked list does not require such continues memory locations.which requires the size specified should be there in memory.

thank you for reading my answer anu mohan aamh04

Answer 4

For efficient storage of information the trees are used.