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38536 results in Cambridge Textbooks

Page 1177 of 1927

  • 7 - Theoretical Issues: Modeling Word-Formation

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 162-197

  • Summary

    In this chapter theories are introduced that try to find principled answers to three central problems of morphology. We will first examine approaches that try to model the interaction of phonology and morphology. This is followed by a treatment of a related problem, the ordering of affixes. In the final part of the chapter we discuss how different morphological theories conceptualize the form and nature of word-formation rules. This discussion includes word-based and morpheme-based approaches as well as computational approaches (analogical modeling and Naive Discriminative Learning).

  • 13 - Physical Database Organization

  • from Part III - Physical Data Storage, Transaction Management, and Database Access
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 395-429

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • grasp the basic concepts of physical database organization;

  • • identify various database access methods;

  • • understand how individual devices can be pooled and managed as so-called enterprise storage subsystems;

  • • understand the importance of business continuity.

    • Opening Scenario

    Now that Sober knows what indexes it needs, it wants to understand how these indexes can be implemented in SQL. The company is also curious to find out how the query optimizer works and how it decides on the access path to the data for a given query. Sober wonders what type of storage hardware it should adopt. Finally, the company wants to figure out how it can guarantee its uninterrupted functioning, despite possible planned or unplanned downtime of the hard- and software.

    This chapter deals with physical database organization in its broadest sense. A primary focus is on physical database design – the translation of a logical data model into an internal data model, including the design of indexes to speed up data access. In this respect, this chapter builds on the insights gained from Chapter 12 in relation to physical record and file organization. However, we also zoom out to other concerns of physical data storage, such as technological and management aspects, as well as the important area of business continuity.

    First, we discuss the concepts of tablespaces and index spaces, as well as other basic building blocks of physical database organization. The principles of file organization acquired in the previous chapter are then applied in the context of database organization. Here, we deal with the role of the query optimizer and how the latter uses indexes and other techniques to determine the optimal access plan to execute a query. We also pay particular attention to different alternatives for join implementation. In the second half of this chapter, we return to storage hardware, but now from a more global perspective than in Chapter 12. We deal with RAID technology and different approaches to networked storage, such as SAN and NAS. We conclude with a discussion on how these techniques can be applied in the context of business continuity. By no means do we claim exhaustiveness with respect to the topics covered in this chapter. Rather, we aim to provide the reader with a broad perspective on the many angles and concerns of physical data storage and management.

  • 6 - Relational Databases: The Relational Model

  • from Part II - Types of Database Systems
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 104-145

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • understand the basic concepts of the relational model;

  • • differentiate between different types of keys and identify their role in the relational model;

  • • understand how normalization can be used to make sure a relational data model has no redundancies or inconsistencies;

  • • map a conceptual ER model to a relational model and identify any loss of semantics;

  • • map a conceptual EER model to a relational model and identify any loss of semantics.

    • Opening Scenario

    Starting from the EER conceptual data model developed in Chapter 3, Sober wants to proceed to the next step of database design. The company wants to map the EER model to a logical relational model and needs to understand what semantics gets lost in the mapping process.

    Relational databases implement the relational model, which is one of the most popular logical and internal data models in use nowadays. It was first formalized by Edgar F. Codd in his seminal paper “A relational model of data for large shared data banks”, which appeared in the well-respected journal Communications of the ACM in 1970. In this chapter we first introduce the basic concepts of the relational model and then formally define them in the next section. This is followed by an overview of the different types of keys, which are an essential building block of the relational model. The relational constraints are summarized next, followed by an example of a relational data model. Normalization will also be reviewed as a procedure to remove redundancies and anomalies from a relational data model. After having introduced the need for normalization and some informal guidelines, we zoom into functional dependencies and prime attribute types and discuss how both can be used during a multi-step normalization procedure. To conclude, we discuss how to map both ER and EER conceptual data models to a logical relational data model. The next chapter then zooms into SQL, which is the DDL and DML used by relational databases.

    Drill Down

    Edgar F. Codd was an English computer scientist (19 August 1923–18 April 2003) who laid the foundation of the relational model while working for IBM. He received the Turing Award in 1981 and was inducted as a Fellow of the Association for Computing Machinery (ACM) in 1994.

  • 6 - Compounding

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 131-161

  • Summary

    This chapter is concerned with compounds. Section 6.1 focuses on the basic characteristics of compounds, investigating the kinds of element compounds are made of, their internal structure, headedness, and stress patterns. This is followed by descriptions of individual compounding patterns and the discussion of the specific empirical and theoretical problems these patterns pose. In particular, nominal, adjectival, verbal, and neoclassical compounds are examined, followed by an exploration of the syntax-morphology boundary.

  • 2 - Studying Complex Words

  • Ingo Plag, Heinrich-Heine-Universität Düsseldorf
  • Book:
    Word-Formation in English
    Published online:
    30 April 2019
    Print publication:
    12 July 2018, pp 20-43

  • Summary

    This chapter discusses in some detail the problems that arise with the implementation of the basic notions introduced in chapter 1 in the actual analysis of word structure in English. First, the notion of the morpheme is scrutinized with its problems of the mapping of form and meaning. Then the phenomenon of base and affix allomorphy is introduced, followed by a discussion of the notion of ‘word-formation rule’. Finally, cases of multiple affixation and compounding are analyzed.

  • 14 - Basics of Transaction Management

  • from Part III - Physical Data Storage, Transaction Management, and Database Access
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 430-457

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • understand the concepts of transactions, recovery, and concurrency control;

  • • identify the various steps of a transaction lifecycle as well as the DBMS components involved and the role of the logfile;

  • • discern different types of failures and how to deal with them;

  • • understand different types of concurrency problems as well as the importance of schedules, serial schedules, and serializable schedules;

  • • discern the differences between optimistic and pessimistic schedulers;

  • • grasp the importance of locking and locking protocols;

  • • understand the responsibility of the DBMS's transaction management facilities to ensure the ACID properties of a transaction.

    • Opening Scenario

    Since many users will interact simultaneously with Sober's database, the company wants to understand any problems that may occur. Furthermore, Sober also wants to mitigate the risks of various types of failures that may make its data incorrect.

    The majority of databases in actual organizational settings are multi-user databases. This implies that many applications and users can access the data in the database in parallel. This concurrent access to the same data, if not managed properly, may induce different types of anomalies or unexpected problems. Moreover, various kinds of errors or calamities may occur in the respective DBMS components or its environment – such as the operating system, the applications interacting with the DBMS, or the storage subsystem – possibly rendering the database data into an inconsistent state. Fortunately, most database systems provide a realm of transparent, although often configurable, solutions to avoid or otherwise deal with such problems. In this way, the DBMS supports the ACID (Atomicity, Consistency, Isolation, Durability) properties already mentioned in Chapter 1. At the heart of these solutions are the concepts of transactions and transaction management, recovery, and concurrency control. In this chapter, we first introduce each of these concepts. Then, we focus in more detail on transaction management and the DBMS components involved. After that, we discuss recovery and the different techniques to deal with calamities in the DBMS or application program, as well as the storage media. Finally, we describe in detail how concurrency control techniques, in interplay with transaction management and recovery, guarantee seamless concurrent access by multiple users to shared data.

  • 17 - Data Warehousing and Business Intelligence

  • from Part IV - Data Warehousing, Data Governance, and (Big) Data Analytics
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 551-589

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • understand the differences between operational and tactical/strategic decision-making;

  • • define a data warehouse in terms of its key characteristics;

  • • discern different types of data warehouse schemas;

  • • understand the key steps of the extraction, transformation, and loading process;

  • • define a data mart in terms of its key characteristics;

  • • understand the advantages and disadvantages of virtual data warehouses and virtual data marts;

  • • define an operational data store;

  • • discern the differences between data warehouses and data lakes;

  • • understand the applications of business intelligence by means of query and reporting, pivot tables, and on-line analytical processing.

    • Opening Scenario

    In addition to using its data for day-to-day operational activities, Sober wants to leverage it for both tactical and strategical decision-making. More specifically, the company wants to get a thorough insight in its sales numbers and how these vary on a quarterly basis, per type of service (ride-hailing versus ride-sharing) and per type of car (Sober car or not). By doing so, Sober wants to better understand where it can grow and identify interesting opportunities. The company does not believe it can use its existing relational data model for this since turning the above questions into SQL queries might be too cumbersome. The principals think a new type of data structure is needed to more efficiently answer the above business questions. Considering the limitations of its current model, what would you recommend Sober to do?

    Until this point, we have largely focused on storing data in the most optimal way, ensuring their integrity, as much as possible, at all times. A next obvious question is what can we do with these data from a business perspective? In this chapter, we discuss how to take data and extract valuable new business insights from it. We start by zooming into the various levels of corporate decisionmaking and how this relates to data requirements that support these decisions. This will bring us to the concept of a data warehouse, a massive consolidated data store that we formally define and extensively discuss in terms of data model, design, and development. We contrast data warehousing with some newer developments, such as virtualization, data lakes, and indicate synergies.

  • 8 - Object-Oriented Databases and Object Persistence

  • from Part II - Types of Database Systems
  • Wilfried Lemahieu, KU Leuven, Belgium, Seppe vanden Broucke, KU Leuven, Belgium, Bart Baesens, KU Leuven, Belgium
  • Book:
    Principles of Database Management
    Published online:
    17 August 2019
    Print publication:
    12 July 2018, pp 207-230

  • Summary

    Chapter Objectives

    In this chapter, you will learn to:

  • • use advanced concepts of object orientation, such as method overloading, inheritance, method overriding, polymorphism, and dynamic binding;

  • • identify various strategies to ensure object persistence;

  • • understand the key components of an OODBMS;

  • • understand the ODMG standard and its object model;

  • • use the ODMG object definition language (ODL) to define object types;

  • • use the ODMG object query language (OQL) to formulate queries;

  • • implement the ODMG standard through language bindings;

  • • evaluate OODBMSs against RDBMSs.

    • Opening Scenario

    Sober has noted that many database applications are being developed using programming languages such as Java, Python, and C++. It found out that many languages are based on the object-oriented paradigm. The company wants to know what this entails and whether this could have any implications and/or potential for its database and choice of DBMS.

    The object-oriented (OO) paradigm was first introduced by programming languages such as C++, Eiffel, and Smalltalk. Due to its expressive modeling power and formal semantics, the principles of OO have also been widely used in software development methodologies. However, for data storage and management, the adoption of OO proved less straightforward. In this chapter, we discuss various approaches to object persistence. First, we refresh the basic concepts of OO, many of which have been covered in Chapter 3. This will be followed by a discussion of advanced OO concepts such as method overloading, inheritance, method overriding, polymorphism, and dynamic binding. Next, we review the basic principles of object persistence. We then discuss object-oriented database management systems (OODBMSs), which is the core of this chapter. We conclude with evaluating OODBMSs and demonstrating their impact on the emergence of object-relational mapping (ORM) frameworks, which facilitate the persistence of objects into RDBMSs. Due to its popularity and ease of use, we use Java as the OO language for the examples.

    Recap: Basic Concepts of OO

    In object-oriented (OO) programming, an application consists of a series of objects that request services from each other. Each object is an instance of a class that contains a blueprint description of all the object's characteristics. Contrary to procedural programming, an object bundles both its variables (which determine its state) and its methods (which determine its behavior) in a coherent way.

Page 1177 of 1927