Contents at a Glance Foreword About the Author About the Technical Reviewers Acknowledgments Introduction CHAPTER 1 What Do You Mean by Cost? CHAPTER 2 Tablescans CHAPTER 3 Single Table Selectivity CHAPTER 4 Simple B-tree Access CHAPTER 5 The Clustering Factor CHAPTER 6 Selectivity Issues CHAPTER 7 Histograms CHAPTER 8 Bitmap Indexes CHAPTER 9 Query Transformation CHAPTER 10 Join Cardinality CHAPTER 11 Nested Loops CHAPTER 12
XQuery can be a challenging topic to teach. There is only enough time to cover
what it is, what it can do, and its basic syntax, but not in any depth. This
module leaves the detailed coverage of XQuery for later courses. Just as Course
1913A, Exchanging and Transforming Data Using XML and XSLT, is a fiveday
course on Extensible Stylesheet Language Transformations (XSLT), it is
possible to devote a full five-day course to XQuery after it is fully specified and
achieves W3C Recommendation status.
Những nhà phát triển có thể sử dụng LINQ với bất kỳ dữ liệu nguồn nào. Họ hoàn toàn có thể đưa ra thao tác truy vấn trong ngôn ngữ lập trình mà họ đã chọn. Những kết quả truy vấn dữ liệu được biến đổi/ sắp đặt(transform/shape) vào bên trong bất kỳ định dạng nào mà họ muốn, và sau đó họ có thể dễ dàng thao tác trên những dữ liệu đó.
One of transformation's most primitive forms is the transformation of character sequences
otherwise known as strings. Unlike the ancient language SNOBOL or the relatively modern Perl,
XSLT was not specifically designed with string manipulation in mind. However, Chapter 1 shows
that almost anything one wants to do with strings can be done within the confines of XSLT.
Continuous queries are persistent queries that allow users to
receive new results when they become available. While
continuous query systems can transform a passive web into an
active environment, they need to be able to support millions of
queries due to the scale of the Internet. No existing systems have
achieved this level of scalability. NiagaraCQ addresses this
problem by grouping continuous queries based on the
observation that many web queries share similar structures.
This chapter describes the process by which queries are executed efficiently by a database system. Query processing refers to the range of activities involved in extracting data from a database. The activities include translation of queries in high-level database languages into expressions that can be used at the physical level of the file system, a variety of query-optimizing transformations, and actual evaluation of queries.
Chapter 13 describes how queries are optimized. This chapter presents the following content: Transformation of relational expressions, catalog information for cost estimation, statistical information for cost estimation, cost-based optimization, dynamic programming for choosing evaluation plans, materialized views.
This manual describes Oracle XML DB, and how it stores, generates, manipulates,
manages, and queries XML in the database using Oracle XML DB.
After introducing you to the heart of Oracle XML DB, namely the XMLType
framework and Oracle XML DB repository, the manual provides a brief introduction to
design criteria to consider when planning your Oracle XML DB application. It
provides examples of how and where you can use Oracle XML DB.
This session will introduce you to SQL Server and guide you through the
installation process step-by-step. It explains hardware and software requirements
and the reasons for making necessary choices along the way. The final
sidebar comparing SQL Server to other major players on the database market lists
the costs and benefits of various database-system implementations.
Publish/subscribe systems have demonstrated the ability
to scale to large numbers of users and high data rates
when providing content-based data dissemination services
on the Internet. However, their services are limited
by the data semantics and query expressiveness that they
These limitations arise because the P2P world is lacking in the areas of semantics, data transformation, and data
relationships, yet these are some of the core strengths of the data management community. Queries, views, and
integrity constraints can be used to express relationships between existing objects and to deﬁne new objects in terms
of old ones. Complex queries can be posed across multiple sources, and the results of one query can be materialized
and used to answer other queries.
A data warehouse is a relational database designed for query and analysis rather than
for transaction processing. It usually contains historical data derived from transaction
data, but it can include data from other sources. It separates analysis workload from
transaction workload and enables an organization to consolidate data from several
You must load your data warehouse regularly so that it can serve its purpose of
facilitating business analysis. To do this, data from one or more operational systems
must be extracted and copied into the warehouse. The process of extracting data from
source systems and bringing it into the data warehouse is commonly called ETL,
which stands for extraction, transformation, and loading.
A materialized view provides access to table data by storing the results of a query in a
separate schema object.
The paper considers how to scale up dialogue protocols to multilogue, settings with multiple conversationalists. We extract two benchmarks to evaluate scaled up protocols based on the long distance resolution possibilities of nonsentential utterances in dialogue and multilogue in the British National Corpus. In light of these benchmarks, we then consider three possible transformations to dialogue protocols, formulated within an issue-based approach to dialogue management. We show that one such transformation yields protocols for querying and assertion that fulﬁll these benchmarks. ...
In responding to the guidelines established by the session chairman of this panel, three of the five topics he set forth will be discussed. These include aggregate functions and quantity questions, querying semantically complex fields, and multi-file queries. As we will make clear in the sequel, the transformational apparatus utilized in the TQA Question Answering System provides a principled basis for handling these and many other problems i n natural language access to databases.
If a q.a. system tries to transform an English question directly into the simplest possible formulation of the corresponding data base query, discrepancies between the English lexicon and the structure of the data base cannot be handled well. To be able to deal with such discrepancies in a systematic way, the PHLIQAI system distinguishes different levels of semantic representation; it contains modules which translate from one level to another, as well as a module which simplifies expressions within one level.
In Information Retrieval (IR) in general and Question Answering (QA) in particular, queries and relevant textual content often signiﬁcantly differ in their properties and are therefore difﬁcult to relate with traditional IR methods, e.g. key-word matching. In this paper we describe an algorithm that addresses this problem, but rather than looking at it on a term matching/term reformulation level, we focus on the syntactic differences between questions and relevant text passages.
This paper explores the use of clickthrough data for query spelling correction. First, large amounts of query-correction pairs are derived by analyzing users' query reformulation behavior encoded in the clickthrough data. Then, a phrase-based error model that accounts for the transformation probability between multi-term phrases is trained and integrated into a query speller system.
Chapter 10 describes the XML language, and then presents different ways of expressing queries on data represented in XML,and transforming XMLdata from one form to another. This chapter presents the following content: Structure of XML data, XML document schema, querying and transformation, application program interfaces to XML, storage of XML data, XML applications.