Database System Indexing TELU PDF

Database System 03 | Indexing Tahun Ajar Ganjil 2024/2025 Oleh: Tim Dosen  Students knows the basic concepts of indexing GOALS OF...

Database System 03 | Indexing Tahun Ajar Ganjil 2024/2025 Oleh: Tim Dosen  Students knows the basic concepts of indexing GOALS OF Students understand how to organize B+-Tree Index Files MEETING Students can create indexes on the DBMS to speed up searching performance 9 /1 0/ 2 02 4 Storage Management 2 OUTLINES Basic Concepts Ordered Indices B+-Tree Index Files Creation of Indices 9 /1 0/ 2 02 4 Storage Management 3  BASIC CONCEPTS 9 /1 0/ 2 02 4 4 BASIC CONCEPTS Indexing mechanisms used to speed up access to desired data. – E.g., author catalog in library Search Key - attribute to set of attributes used to look up records in a file. An index file consists of records (called index entries) of the form: search-key pointer Index files are typically much smaller than the original file Two basic kinds of indices: – Ordered indices: search keys are stored in sorted order – Hash indices: search keys are distributed uniformly across “buckets” using a “hash function”. ORDERED INDICES In an ordered index, index entries are stored sorted on the search key value. Clustering index: in a sequentially ordered file, the index whose search key specifies the sequential order of the file. – Also called primary index – The search key of a primary index is usually but not necessarily the primary key. Secondary index: an index whose search key specifies an order different from the sequential order of the file. Also called nonclustering index. Index-sequential file: sequential file ordered on a search key, with a clustering index on the search key. DENSE INDEX FILES Dense index — Index record appears for every search-key value in the file. E.g. index on ID attribute of instructor relation D E N S E I N D E X F I L E S ( C O N T. ) Dense index on dept_name, with instructor file sorted on dept_name S PARS E IND EX FI LES Sparse Index: contains index records for only some search-key values. – Applicable when records are sequentially ordered on search-key To locate a record with search-key value K we: – Find index record with largest search-key value < K – Search file sequentially starting at the record to which the index record points S P A R S E I N D E X F I L E S ( C O N T. ) Compared to dense indices: – Less space and less maintenance overhead for insertions and deletions. – Generally slower than dense index for locating records. Good tradeoff: – for clustered index: sparse index with an index entry for every block in file, corresponding to least search-key value in the block. – For unclustered index: sparse index on top of dense index (multilevel index) SECONDARY INDICES EX AMPLE ▪ Secondary index on salary field of instructor ▪ Index record points to a bucket that contains pointers to all the actual records with that particular search-key value. ▪ Secondary indices have to be dense C LU ST ERIN G VS N ON C LU STE RIN G IN D IC ES Indices offer substantial benefits when searching for records. BUT: indices imposes overhead on database modification – when a record is inserted or deleted, every index on the relation must be updated – When a record is updated, any index on an updated attribute must be updated Sequential scan using clustering index is efficient, but a sequential scan using a secondary (nonclustering) index is expensive on magnetic disk – Each record access may fetch a new block from disk – Each block fetch on magnetic disk requires about 5 to 10 milliseconds MULTI LEVE L I NDE X If index does not fit in memory, access becomes expensive. Solution: treat index kept on disk as a sequential file and construct a sparse index on it. – outer index – a sparse index of the basic index – inner index – the basic index file If even outer index is too large to fit in main memory, yet another level of index can be created, and so on. Indices at all levels must be updated on insertion or deletion from the file. M U L T I L E V E L I N D E X ( C O N T. )  B+ -TR E E INDEX FILES 9 /1 0/ 2 02 4 15 B +-T R E E I N D E X F I L E S Disadvantage of indexed-sequential files – Performance degrades as file grows, since many overflow blocks get created. – Periodic reorganization of entire file is required. Advantage of B+-tree index files: – Automatically reorganizes itself with small, local, changes, in the face of insertions and deletions. – Reorganization of entire file is not required to maintain performance. (Minor) disadvantage of B+-trees: – Extra insertion and deletion overhead, space overhead. Advantages of B+-trees outweigh disadvantages – B+-trees are used extensively E X A M P L E O F B +-T R E E B+TREE BASIC Source : https://youtu.be/49P_GDeMDRo 18 B+TREE INSERTION Source : https://youtu.be/h6Mw7_S4ai0 19 B+TREE DELETION Source : https://youtu.be/QrbaQDSuxIM 20  C RE AT I O N O F INDICES 9 /1 0/ 2 02 4 21 CR EAT ION OF IND ICE S Example create index takes_pk on takes (ID,course_ID, year, semester, section) drop index takes_pk Most database systems allow specification of type of index, and clustering. Indices on primary key created automatically by all databases – Why? Some database also create indices on foreign key attributes – Why might such an index be useful for this query: takes ⨝ σname='Shankar' (student) Indices can greatly speed up lookups, but impose cost on updates – Index tuning assistants/wizards supported on several databases to help choose indices, based on query and update workload INDEX DEFINITION IN SQL Create an index: create index on () E.g.,: create index b-index on branch(branch_name) Use create unique index to indirectly specify and enforce the condition that the search key is a candidate key is a candidate key. – Not really required if SQL unique integrity constraint is supported To drop an index: drop index Most database systems allow specification of type of index, and clustering. REFERENCES Silberschatz, Korth, and Sudarshan. Database System Concepts – 7th Edition. McGraw-Hill. 2019. Slides adapted from Database System Concepts Slide. Source: https://www.db-book.com/db7/slides-dir/index.html 24 9 /1 0/ 2 02 4 25