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Space for records is taken out of blocks as required The entire index is prede ned, and allocated at least to an extent that the highest existing record is included Where records do not exist, the index entry value is Null The actual attribute value or key does not appear in the index since the proper index entry is found by the computation index address = indexbegin + (key-1) * P which is similar to the one used for the immediate access to the record without indexes In fact, we have for the index a structure identical to that for the le in Fig 4-1 The storage overhead is reduced for nondense les, since we expect that the index entry, only a pointer of size P , is much smaller than the actual record In this organization the indexes are relatively simple to maintain Data records are easily read and written Updating of records, however, can involve the invalidation of record spaces so that a list of the record spaces that are available for reuse has to be maintained It is easy to permit the storage of variable-length records, since the access algorithm does not depend on a xed value of R A record-marking scheme as described in Sec 2-2-4 will be employed However, if deletion or updating of records of varying size is to be allowed, space management becomes more complex Compression and expansion of the le has to be provided, or a periodic reorganization will be required Since only one index is maintained, few problems occur when a record has to be moved to another position during an update or a reorganization In practice most systems of this type do not allow for variable-length records nor do they warn the user that the e ects are unpredictable 4-1-3 Indexing of Buckets The index organization shown above also can be used to support more complex environments Since this mechanism can provide facilities for variable-length records, it also can be used to store sets or buckets of small records The concept of using buckets allows the use of variable-length records in most le-organization methods Since le storage is organized in terms of blocks, these buckets are de ned again so that they match block sizes as e ectively as possible Not all the records in a key range for a bucket need to be present Records can be packed and searched sequentially in the block or area assigned to the bucket For example, the records numbered 1 to 60 could be assigned to a bucket using the rst index entry, 61 to 120 to the second entry, and so on The buckets accommodate de ned partitions of the index range If many long records are placed into a bucket, it may over ow This type of le is hence a hybrid of features found previously in the direct and the indexed le organizations.

A device configuration describes the arrangement of the various elements and appearances that can be associated with a given device An endless variety of different device configurations may be formed from the possible combinations of physical elements, logical elements, and different appearance types Device configurations are described in terms of a specific base device The following attributes determine the device configuration for a particular device: Physical element (Yes/No) Physical element's other associated logical devices Logical element (Yes/No) Logical element's other associated physical devices Logical element's addressability Logical element's behavior-type Maximum/total appearances Collectively these attributes can be thought of as the device configuration attribute for a specific device This section looks at a number of typical, or foundational, examples that illustrate how device configurations may be formed (In 10 we will look at how these are applied in telephone system implementations)

Sec 4-1

Open Vulnerability and Assessment Language (OVAL)

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A database implementation carries a strong implication of the style of model the user is expected to have of the database Since di erent classes of users will have di erent problems and di erent approaches to their use of the database, no single style of representation may be adequate for all users A major distinction can be made between information-retrieval usage and dataprocessing Another, related, distinction is the predominant type of operational use of the system We distinguish especially operations that retrieve simple items of data versus operations that require retrieval of data collections for further processing We will present these issues in Chap 10, but consider now styles of models and their e ect on the implementation of the database The structural model de ned in Sec 7-3 used relations and connections This model implies that data values can be obtainable by naming relations and attributes, and de ning operations between them Joins along connections have a predictable behavior We distinguish styles based on their stress on relations versus connections We note rst that a fully decomposed normalized model may contain many more relations than the user s personal model needs The use of a submodel, which de nes a speci c and perhaps nonnormalized view, can present the database in a way that is more natural to some users A user s model which ignores the connections is called a relational model The user will de ne explicitly all connections to be used in queries or updates

A logical element only device configuration consists, as the name suggests, of only a logical device element containing non-addressable standard appearances Generally all devices other than station devices have logical element only device configurations The logical element only device configuration illustrated in Figure 4-24 has the following attributes: Physical element: No Physical element's other associated logical devices: N/A Logical element: Yes Logical element's other associated physical devices: None Logical element's addressability: Non-addressable Logical element's behavior-type: Selected Standard Maximum/Total appearances: unlimited4-19

To nd a child of an employee name, both the Children and the Employee relations have to be referenced, and the connection has to be de ned in the query

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