New Storage Systems
17.11 New Storage Systems
In this section, we describe three recent developments in storage systems that are becoming an integral part of most enterprise’s information system architectures.
17.11.1 Storage Area Networks
With the rapid growth of electronic commerce, Enterprise Resource Planning (ERP) systems that integrate application data across organizations, and data ware- houses that keep historical aggregate information (see Chapter 29), the demand for
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become necessary to move from a static fixed data center-oriented operation to a more flexible and dynamic infrastructure for their information processing require- ments. The total cost of managing all data is growing so rapidly that in many instances the cost of managing server-attached storage exceeds the cost of the server itself. Furthermore, the procurement cost of storage is only a small fraction—typi- cally, only 10 to 15 percent of the overall cost of storage management. Many users of RAID systems cannot use the capacity effectively because it has to be attached in a fixed manner to one or more servers. Therefore, most large organizations have moved to a concept called storage area networks (SANs). In a SAN, online storage peripherals are configured as nodes on a high-speed network and can be attached and detached from servers in a very flexible manner. Several companies have emerged as SAN providers and supply their own proprietary topologies. They allow storage systems to be placed at longer distances from the servers and provide differ- ent performance and connectivity options. Existing storage management applica- tions can be ported into SAN configurations using Fiber Channel networks that encapsulate the legacy SCSI protocol. As a result, the SAN-attached devices appear as SCSI devices.
Current architectural alternatives for SAN include the following: point-to-point connections between servers and storage systems via fiber channel; use of a fiber channel switch to connect multiple RAID systems, tape libraries, and so on to servers; and the use of fiber channel hubs and switches to connect servers and stor- age systems in different configurations. Organizations can slowly move up from simpler topologies to more complex ones by adding servers and storage devices as needed. We do not provide further details here because they vary among SAN ven- dors. The main advantages claimed include:
Flexible many-to-many connectivity among servers and storage devices using fiber channel hubs and switches
Up to 10 km separation between a server and a storage system using appro- priate fiber optic cables
Better isolation capabilities allowing nondisruptive addition of new periph- erals and servers
SANs are growing very rapidly, but are still faced with many problems, such as com- bining storage options from multiple vendors and dealing with evolving standards of storage management software and hardware. Most major companies are evaluat- ing SANs as a viable option for database storage.
17.11.2 Network-Attached Storage
With the phenomenal growth in digital data, particularly generated from multime- dia and other enterprise applications, the need for high-performance storage solu- tions at low cost has become extremely important. Network-attached storage (NAS) devices are among the storage devices being used for this purpose. These devices are, in fact, servers that do not provide any of the common server services,
17.11 New Storage Systems 623
amounts of hard-disk storage space to be added to a network and can make that space available to multiple servers without shutting them down for maintenance and upgrades. NAS devices can reside anywhere on a local area network (LAN) and may be combined in different configurations. A single hardware device, often called the NAS box or NAS head, acts as the interface between the NAS system and net- work clients. These NAS devices require no monitor, keyboard, or mouse. One or more disk or tape drives can be attached to many NAS systems to increase total capacity. Clients connect to the NAS head rather than to the individual storage devices. An NAS can store any data that appears in the form of files, such as e-mail boxes, Web content, remote system backups, and so on. In that sense, NAS devices are being deployed as a replacement for traditional file servers.
NAS systems strive for reliable operation and easy administration. They include built-in features such as secure authentication, or the automatic sending of e-mail alerts in case of error on the device. The NAS devices (or appliances, as some ven- dors refer to them) are being offered with a high degree of scalability, reliability, flexibility, and performance. Such devices typically support RAID levels 0, 1, and 5. Traditional storage area networks (SANs) differ from NAS in several ways. Specifically, SANs often utilize Fiber Channel rather than Ethernet, and a SAN often incorporates multiple network devices or endpoints on a self-contained or private LAN, whereas NAS relies on individual devices connected directly to the existing public LAN. Whereas Windows, UNIX, and NetWare file servers each demand spe- cific protocol support on the client side, NAS systems claim greater operating sys- tem independence of clients.
17.11.3 iSCSI Storage Systems
A new protocol called iSCSI (Internet SCSI) has been proposed recently. It allows clients (called initiators) to send SCSI commands to SCSI storage devices on remote channels. The main advantage of iSCSI is that it does not require the special cabling needed by Fiber Channel and it can run over longer distances using existing network infrastructure. By carrying SCSI commands over IP networks, iSCSI facilitates data transfers over intranets and manages storage over long distances. It can transfer data over local area networks (LANs), wide area networks (WANs), or the Internet.
iSCSI works as follows. When a DBMS needs to access data, the operating system generates the appropriate SCSI commands and data request, which then go through encapsulation and, if necessary, encryption procedures. A packet header is added before the resulting IP packets are transmitted over an Ethernet connection. When a packet is received, it is decrypted (if it was encrypted before transmission) and dis- assembled, separating the SCSI commands and request. The SCSI commands go via the SCSI controller to the SCSI storage device. Because iSCSI is bidirectional, the protocol can also be used to return data in response to the original request. Cisco and IBM have marketed switches and routers based on this technology.
iSCSI storage has mainly impacted small- and medium-sized businesses because of its combination of simplicity, low cost, and the functionality of iSCSI devices. It
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instead benefit from their familiarity with the IP protocol and Ethernet hardware. iSCSI implementations in the data centers of very large enterprise businesses are slow in development due to their prior investment in Fiber Channel-based SANs.
iSCSI is one of two main approaches to storage data transmission over IP networks. The other method, Fiber Channel over IP (FCIP), translates Fiber Channel control codes and data into IP packets for transmission between geographically distant Fiber Channel storage area networks. This protocol, known also as Fiber Channel tunneling or storage tunneling, can only be used in conjunction with Fiber Channel technology, whereas iSCSI can run over existing Ethernet networks.
The latest idea to enter the enterprise IP storage race is Fiber Channel over Ethernet (FCoE) , which can be thought of as iSCSI without the IP. It uses many ele- ments of SCSI and FC (just like iSCSI), but it does not include TCP/IP components. This promises excellent performance, especially on 10 Gigabit Ethernet (10GbE), and is relatively easy for vendors to add to their products.
Parts
» Fundamentals_of_Database_Systems,_6th_Edition
» Characteristics of the Database Approach
» Advantages of Using the DBMS Approach
» A Brief History of Database Applications
» Schemas, Instances, and Database State
» The Three-Schema Architecture
» The Database System Environment
» Centralized and Client/Server Architectures for DBMSs
» Classification of Database Management Systems
» Domains, Attributes, Tuples, and Relations
» Key Constraints and Constraints on NULL Values
» Relational Databases and Relational Database Schemas
» Integrity, Referential Integrity, and Foreign Keys
» Update Operations, Transactions, and Dealing with Constraint Violations
» SQL Data Definition and Data Types
» Specifying Constraints in SQL
» The SELECT-FROM-WHERE Structure of Basic SQL Queries
» Ambiguous Attribute Names, Aliasing, Renaming, and Tuple Variables
» Substring Pattern Matching and Arithmetic Operators
» INSERT, DELETE, and UPDATE Statements in SQL
» Comparisons Involving NULL and Three-Valued Logic
» Nested Queries, Tuples, and Set/Multiset Comparisons
» The EXISTS and UNIQUE Functions in SQL
» Joined Tables in SQL and Outer Joins
» Grouping: The GROUP BY and HAVING Clauses
» Discussion and Summary of SQL Queries
» Specifying General Constraints as Assertions in SQL
» Introduction to Triggers in SQL
» Specification of Views in SQL
» View Implementation, View Update, and Inline Views
» Schema Change Statements in SQL
» Sequences of Operations and the RENAME Operation
» The UNION, INTERSECTION, and MINUS Operations
» The CARTESIAN PRODUCT (CROSS PRODUCT) Operation
» Variations of JOIN: The EQUIJOIN and NATURAL JOIN
» Additional Relational Operations
» Examples of Queries in Relational Algebra
» The Tuple Relational Calculus
» The Domain Relational Calculus
» Using High-Level Conceptual Data Models
» Entity Types, Entity Sets, Keys, and Value Sets
» Relationship Types, Relationship Sets, Roles, and Structural Constraints
» ER Diagrams, Naming Conventions, and Design Issues
» Example of Other Notation: UML Class Diagrams
» Relationship Types of Degree Higher than Two
» Subclasses, Superclasses, and Inheritance
» Constraints on Specialization and Generalization
» Specialization and Generalization Hierarchies
» Modeling of UNION Types Using Categories
» A Sample UNIVERSITY EER Schema, Design Choices, and Formal Definitions
» Data Abstraction, Knowledge Representation, and Ontology Concepts
» ER-to-Relational Mapping Algorithm
» Discussion and Summary of Mapping for ER Model Constructs
» Mapping EER Model Constructs
» The Role of Information Systems
» The Database Design and Implementation Process
» Use of UML Diagrams as an Aid to Database Design Specification 6
» Rational Rose: A UML-Based Design Tool
» Automated Database Design Tools
» Introduction to Object-Oriented Concepts and Features
» Object Identity, and Objects versus Literals
» Complex Type Structures for Objects and Literals
» Encapsulation of Operations and Persistence of Objects
» Type Hierarchies and Inheritance
» Other Object-Oriented Concepts
» Object-Relational Features: Object Database Extensions to SQL
» Overview of the Object Model of ODMG
» Built-in Interfaces and Classes in the Object Model
» Atomic (User-Defined) Objects
» Extents, Keys, and Factory Objects
» The Object Definition Language ODL
» Differences between Conceptual Design of ODB and RDB
» Mapping an EER Schema to an ODB Schema
» Query Results and Path Expressions
» Overview of the C++ Language Binding in the ODMG Standard
» Structured, Semistructured, and Unstructured Data
» XML Hierarchical (Tree) Data Model
» Well-Formed and Valid XML Documents and XML DTD
» XPath: Specifying Path Expressions in XML
» XQuery: Specifying Queries in XML
» Extracting XML Documents from
» Database Programming: Techniques
» Retrieving Single Tuples with Embedded SQL
» Retrieving Multiple Tuples with Embedded SQL Using Cursors
» Specifying Queries at Runtime Using Dynamic SQL
» SQLJ: Embedding SQL Commands in Java
» Retrieving Multiple Tuples in SQLJ Using Iterators
» Database Programming with SQL/CLI Using C
» JDBC: SQL Function Calls for Java Programming
» Database Stored Procedures and SQL/PSM
» PHP Variables, Data Types, and Programming Constructs
» Overview of PHP Database Programming
» Imparting Clear Semantics to Attributes in Relations
» Redundant Information in Tuples and Update Anomalies
» Normal Forms Based on Primary Keys
» General Definitions of Second and Third Normal Forms
» Multivalued Dependency and Fourth Normal Form
» Join Dependencies and Fifth Normal Form
» Inference Rules for Functional Dependencies
» Minimal Sets of Functional Dependencies
» Properties of Relational Decompositions
» Dependency-Preserving Decomposition
» Dependency-Preserving and Nonadditive (Lossless) Join Decomposition into 3NF Schemas
» Problems with NULL Values and Dangling Tuples
» Discussion of Normalization Algorithms and Alternative Relational Designs
» Further Discussion of Multivalued Dependencies and 4NF
» Other Dependencies and Normal Forms
» Memory Hierarchies and Storage Devices
» Hardware Description of Disk Devices
» Magnetic Tape Storage Devices
» Placing File Records on Disk
» Files of Unordered Records (Heap Files)
» Files of Ordered Records (Sorted Files)
» External Hashing for Disk Files
» Hashing Techniques That Allow Dynamic File Expansion
» Other Primary File Organizations
» Parallelizing Disk Access Using RAID Technology
» Types of Single-Level Ordered Indexes
» Some General Issues Concerning Indexing
» Algorithms for External Sorting
» Implementing the SELECT Operation
» Implementing the JOIN Operation
» Algorithms for PROJECT and Set
» Notation for Query Trees and Query Graphs
» Heuristic Optimization of Query Trees
» Catalog Information Used in Cost Functions
» Examples of Cost Functions for SELECT
» Examples of Cost Functions for JOIN
» Example to Illustrate Cost-Based Query Optimization
» Factors That Influence Physical Database Design
» Physical Database Design Decisions
» An Overview of Database Tuning in Relational Systems
» Transactions, Database Items, Read and Write Operations, and DBMS Buffers
» Why Concurrency Control Is Needed
» Transaction and System Concepts
» Desirable Properties of Transactions
» Serial, Nonserial, and Conflict-Serializable Schedules
» Testing for Conflict Serializability of a Schedule
» How Serializability Is Used for Concurrency Control
» View Equivalence and View Serializability
» Types of Locks and System Lock Tables
» Guaranteeing Serializability by Two-Phase Locking
» Dealing with Deadlock and Starvation
» Concurrency Control Based on Timestamp Ordering
» Multiversion Concurrency Control Techniques
» Validation (Optimistic) Concurrency
» Granularity of Data Items and Multiple Granularity Locking
» Using Locks for Concurrency Control in Indexes
» Other Concurrency Control Issues
» Recovery Outline and Categorization of Recovery Algorithms
» Caching (Buffering) of Disk Blocks
» Write-Ahead Logging, Steal/No-Steal, and Force/No-Force
» Transaction Rollback and Cascading Rollback
» NO-UNDO/REDO Recovery Based on Deferred Update
» Recovery Techniques Based on Immediate Update
» The ARIES Recovery Algorithm
» Recovery in Multidatabase Systems
» Introduction to Database Security Issues 1
» Discretionary Access Control Based on Granting and Revoking Privileges
» Mandatory Access Control and Role-Based Access Control for Multilevel Security
» Introduction to Statistical Database Security
» Introduction to Flow Control
» Encryption and Public Key Infrastructures
» Challenges of Database Security
» Distributed Database Concepts 1
» Types of Distributed Database Systems
» Distributed Database Architectures
» Data Replication and Allocation
» Example of Fragmentation, Allocation, and Replication
» Query Processing and Optimization in Distributed Databases
» Overview of Transaction Management in Distributed Databases
» Overview of Concurrency Control and Recovery in Distributed Databases
» Current Trends in Distributed Databases
» Distributed Databases in Oracle 13
» Generalized Model for Active Databases and Oracle Triggers
» Design and Implementation Issues for Active Databases
» Examples of Statement-Level Active Rules
» Time Representation, Calendars, and Time Dimensions
» Incorporating Time in Relational Databases Using Tuple Versioning
» Incorporating Time in Object-Oriented Databases Using Attribute Versioning
» Temporal Querying Constructs and the TSQL2 Language
» Spatial Database Concepts 24
» Multimedia Database Concepts
» Clausal Form and Horn Clauses
» Datalog Programs and Their Safety
» Evaluation of Nonrecursive Datalog Queries
» Introduction to Information Retrieval
» Types of Queries in IR Systems
» Evaluation Measures of Search Relevance
» Web Analysis and Its Relationship to Information Retrieval
» Analyzing the Link Structure of Web Pages
» Approaches to Web Content Analysis
» Trends in Information Retrieval
» Data Mining as a Part of the Knowledge
» Goals of Data Mining and Knowledge Discovery
» Types of Knowledge Discovered during Data Mining
» Market-Basket Model, Support, and Confidence
» Frequent-Pattern (FP) Tree and FP-Growth Algorithm
» Other Types of Association Rules
» Approaches to Other Data Mining Problems
» Commercial Data Mining Tools
» Data Modeling for Data Warehouses
» Difficulties of Implementing Data Warehouses
» Grouping, Aggregation, and Database Modification in QBE
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