Lecture
Indexing (cf. in accelerating the operation of searching records in a table, search, extraction, modifications, sorting) in ind. Lists i'm an opred attributes with decree. The database page contains the strings where the meetings are corresponding to. The indexed file is the main file for which the index file is created. Index f — f particular type in which. Every record status from 2 values: dan. and record number index. Data provided by the field that was indexed, and the pointer is impl. bind to the corresponding entry in the index file. If f. big, then ind. f. also. Not recommended create ind for all fields, and for the first. keys for ext. The keys. Basics advantages - means speeding up the sampling process or retrieved. Dun., DOS disadvantage. - slowed down the update process given, because for every added new zap in the indexed file need to add new. index file. Poet at vyb. fields it is important to know which one of the 2 will show. more important: sampling speed or speed. processing. In SQL-Create Index.
Features of hashing technology. Hashing is called a technologist. quick access to store records based on preset value. some fields. excl. from indexing only 1 hash field is used). With Hashir, some function is used to determine location. any element dan. The main features of Heshire are: 1. each store the database record located at the address that was calculated with. special hash function based on value. some dan fields records 2. for saved. zap in a DBMS calculated hash address new. zap., after which the program manager disk memory placed This entry is a calculated address. 3. for extracted. need zap on set. value hash fields in the DBMS from the beginning. calculate hash add., then in prog. The disk drive is sent with a request to the memory. Records are calculated by addr. Basics advantages Hash-Ia zakl-Xia in speed of access. to the data. Minus - the complexity of the choice of eligible. hash functions., overflow., ned. filled pages
Compression of data based on differences.
In order to reduce the space required to store a certain set of data, compression technologies are often used. At the same time, as a result, not only disk space is saved, but also the number of disk I / O operations, since access to smaller data requires less disk I / O operations. On the other hand, unpacking and extracting compressed data requires some additional manipulation, but in general the advantages of reducing I / O operations can compensate for the disadvantages associated with additional data processing.
Compression technologies are based on the low probability that the data has a completely random structure. The most common is a compression technology based on differences, in which a value is replaced with information about its differences from the previous value. It should be noted that for the implementation of this technology, it is required to place the data sequentially, since to unpack it, it is necessary to have the value of the previous value. Such compression is very effective for data that requires sequential access, for example, for entries in a single-level list. Moreover, in such cases, along with the data, pointers are also allowed to be compressed. The fact is that if the logical sequence in the file corresponds to the physical sequence of the data on the disk, then the adjacent pointers will differ slightly from each other, which means that compressing the pointers can be very useful and effective. The essence of compression based on differences lies in the fact that it provides for the replacement of some values by information about its differences from the previous values.
Hierarchical compression. In order to reduce the space required to store a certain set of data, compression technologies are often used. At the same time, as a result, not only disk space is saved, but also the number of disk I / O operations, since access to smaller data requires less disk I / O operations. On the other hand, unpacking and extracting compressed data requires some additional manipulation, but in general the advantages of reducing I / O operations can compensate for the disadvantages associated with additional data processing.
Hierarchical compressed - each. record breaking on constant. and change. Constant. - coded.
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Databases, knowledge and data warehousing. Big data, DBMS and SQL and noSQL
Terms: Databases, knowledge and data warehousing. Big data, DBMS and SQL and noSQL