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Jun-Ki Min. 2  Logical and physical data independence allows the user to focus on logical aspects and not to worry about physical details  However,

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Presentation on theme: "Jun-Ki Min. 2  Logical and physical data independence allows the user to focus on logical aspects and not to worry about physical details  However,"— Presentation transcript:

1 Jun-Ki Min

2 2  Logical and physical data independence allows the user to focus on logical aspects and not to worry about physical details  However, the physical structure of the database affects the performance  Thus, the physical schema must be carefully designed  random access time of DISK -data access time -seek time + rotational delay+ block transfer time  Mechanical procedure ◦ Reduce # of disk I/O

3 3  database Procedure Record request by Request stored record to file manager file manager finds a block containing the record  Request a page to disk manager disk manager  Order disk I/O DBMS users stored database file manager disk manager Request record resutl Request Stored record Return record Request Page Return page Transfer block DISK I/O OS

4 4  Support basic I/O service ◦ Reposible of all DISK I/OKnow all physical disk address ◦ A component of operating system  Support file manager ◦ file manager can be see disk as sets of pages ◦ In page set, there is free space page set ◦ Each page set has unique page set ID ◦ Each page is unique page number  Manage DISK ◦ Mapp page number to physical address   support independence of file manager

5 5  Support that DBMS vies disk as set of stored files  stored file ◦ A file is a sequence of records, where each record is a collection of data values (or data items). ◦ A set of same typed (stored) records ◦ Each page set stores several file ◦ Identified by file name or file ID  stored record ◦ Identified by record number or record identifier(RID) ◦ It is unique in DISK ◦

6 6  disk manager’s page management ◦ Function of disk manger  File manager performs logical page I/O rather than physical disk I/O  Example of University DB ◦ Page set consist of 28 pages ◦ Each record is a page.

7 7 snocnograde E1: 100C413A E2: 100E412A E3: 200C123B E4: 300C312A E5: 300C324C E6: 300C413A E7: 400C312A E8: 400C324A E9: 400C413B E10: 400E412C E11: 500C312B snosnameyeardept S1: 100 나수영 4 컴퓨터 S2: 200 이찬수 3 전기 S3: 300 정기태 1 컴퓨터 S4: 400 송병길 4 컴퓨터 S5: 500 박종화 2 산공 enroll cnocnameCpoi nt professor C1: C123 프로그래밍 3 김성국 C2: C312 자료 구조 3 황수관 C3: C324 화일 구조 3 이규찬 C4: C413 데이타베이스 3 이일로 C5: E412 반 도 체반 도 체 3 홍봉진 student course

8 8  Initial: ◦ A free space page set (1 ~ 27) ◦ Except page 0 : directory  file manager: insert five student records ◦ disk manager : allocate page 1~5 as “student page set" from free space page set ◦ 4 page sets  “studnet"(1~5),  “course"(6~10),  “enroll"(11~21),  “free space" page set (22~27)

9 9

10 10  file manager : insert new stuident S6 (sno 600) ◦ disk manager : get first free page (page 22) from free space page set, and add student page set  file manager : delete student S2 (sno 200) ◦ disk manager : return page 2( S2) to free space page set  file manager : insert new course C6 (E 515) ◦ disk manager : get first free page (page 2), and add course page set  file manager : delete student S4 ◦ disk manager : return page 4(S4) to free space page set

11 11 I : S6 D : S2 I : C6 D : S4 ◦ Physical adjacency is removed

12 12  Hard to represent logical order of page set as physical adjacency  Store control information in page header ◦ next page pointer  Physical address of next page  next page pointer is maintained by disk manager (file manager does not concern about that)

13 13  “next page()”

14 14  disk directory(page set directory) ◦ cylender 0, track 0 ◦ Stores list of all page sets and their first page address  disk directory (page 0) 0 Page set Free space student course enroll address 4 1 6 11

15 15  stored record management ◦ Support that DBMS does not know page I/O ◦ Support handling records  Example ◦ In a page, several records ◦ Logical order of student records follows sno 1) In page p, five student records (S1~ S5) P S1S2S3 S4S5.

16 16 P S1S3S4 S5S7S9 2) DBMS : request insert S9(sno 900)  In page p, S9 stored after S5 3) DBMS : request delete S2  In page p, remove S2 and compact 4) DBMS : request insert S7(sno 700)  S7 locates between S5 and S9  shift S9 and insert.

17 17  RID =  offset= location(# of bytes) of stored record from page start  If location of record is changed, contents of offset is changed without change of RID  At most, two accesses is required to get a record p Record r 5 4 3 2 1 0 p4 record R’s RID Page number offset (slot number) 5 4 3 2 1 0

18 18 File Organization sequential method Index methodHashing method Direct FileMulti-Key FileIndexed sequential File Key sequential File Entry sequential File (pile) multi-list fileInvert File

19  store order is same to logical order of records ◦ heap or pile : entry-sequence file ◦ general : key-sequence file  Entry Sequence file ◦ New records are inserted at the end of the file. ◦ A linear search through the file records is necessary to search for a record.  This requires reading and searching half the file blocks on the average, and is hence quite expensive. ◦ Record insertion is quite efficient. ◦ Reading the records in order of a particular field requires sorting the file records.

20 Slide 13- 20  Key sequential file. ◦ File records are kept sorted by the values of an ordering field. ◦ Insertion is expensive: records must be inserted in the correct order.  It is common to keep a separate unordered overflow (or transact ion) file for new records to improve insertion efficiency; this is p eriodically merged with the main ordered file. ◦ A binary search can be used to search for a record on its ordering field val ue.  This requires reading and searching log 2 of the file blocks on th e average, an improvement over linear search. ◦ Reading the records in order of the ordering field is quite efficient.

21 Slide 13- 21  The following table shows the average access time to access a specific record for a given ty pe of file S1(100)S2(200)S3(300) S4(400)S5(500) S4S1S2 S5S3 entry sequence file key sequence file

22 22 key address K1 K2 K3 Index file Data File  indexed file consists of ◦ index file ◦ data file

23 23  support sequential access and direct access  sequential data file ◦ records are sorted ◦ sequential access method  index ◦ direct access method

24 Slide 14- 24  A single-level index is an auxiliary file that m akes it more efficient to search for a record in the data file.  The index is usually specified on one field of t he file (although it could be specified on seve ral fields)  One form of an index is a file of entries, which is ordered by field value  The index is called an access path on the field.

25 Slide 14- 25  The index file usually occupies considerably less di sk blocks than the data file because its entries are much smaller  A binary search on the index yields a pointer to the file record  Indexes can also be characterized as dense or spar se ◦ A dense index has an index entry for every search key value (and hence every record) in the data file. ◦ A sparse (or nondense) index, on the other hand, has i ndex entries for only some of the search values

26 26  primary index ◦ index with primary key ◦ Defined on an ordered data file ◦ The data file is ordered on a key field ◦ with a key, find a unique record  secondary index ◦ index with secondary key-non key attribute. ◦ with a value, find several records ◦ ex) name  clustering index ◦ The data file is ordered on a non-key field unlike primary index, which requires that the ordering field of the data file have a distinct value for each record. ◦ records having same search key are physically clustered  efficient search ◦ In a data file, one clustering index at most.  nonclustering index


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