PowerPoint PresentationIndexes as Access PathsIndexes as Access Paths (cont.)Types of Single-Level IndexesPrimary Index on the Ordering Key FieldSlide 6Slide 7A Clustering Index ExampleAnother Clustering Index ExampleSlide 10Example of a Dense Secondary IndexExample of a Secondary IndexMulti-Level IndexesA Two-Level Primary IndexSlide 15A Node in a Search Tree with Pointers to Subtrees Below ItSlide 17Dynamic Multilevel Indexes Using B-Trees and B+-TreesDynamic Multilevel Indexes Using B-Trees and B+-Trees (cont.)Difference between B-tree and B+-treeB-tree StructuresThe Nodes of a B+-treeExample of an Insertion in a B+-treeSummaryCopyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-WesleyChapter 18Indexing Structures for FilesCopyright © 2011 Ramez Elmasri and Shamkant NavatheIndexes as Access PathsA single-level index is an auxiliary file that makes it more efficient to search for a record in the data file.The index is usually specified on one field of the file (although it could be specified on several fields)One form of an index is a file of entries <field value, pointer to record>, which is ordered by field valueThe index is called an access path on the field.Copyright © 2011 Ramez Elmasri and Shamkant NavatheIndexes as Access Paths (cont.)The index file usually occupies considerably less disk blocks than the data file because its entries are much smallerA binary search on the index yields a pointer to the file recordIndexes can also be characterized as dense or sparse 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 index entries for only some of the search valuesCopyright © 2011 Ramez Elmasri and Shamkant NavatheTypes of Single-Level IndexesPrimary IndexDefined on an ordered data fileThe data file is ordered on a key fieldIncludes one index entry for each block in the data file; the index entry has the key field value for the first record in the block, which is called the block anchorA similar scheme can use the last record in a block.A primary index is a nondense (sparse) index, since it includes an entry for each disk block of the data file and the keys of its anchor record rather than for every search value.Copyright © 2011 Ramez Elmasri and Shamkant NavathePrimary Index on the Ordering Key FieldCopyright © 2011 Ramez Elmasri and Shamkant NavatheIndexes as Access Paths (cont.)Example: Given the following data file EMPLOYEE(NAME, SSN, ADDRESS, JOB, SAL, ... )Suppose that:record size R=100 bytes block size B=1024 bytesr=30000 recordsThen, we get:blocking factor Bfr= B div R= 1024 div 100= 10 records/blocknumber of file blocks b= (r/Bfr)= (30000/10)= 3000 blocksFor an index on the SSN field, assume the field size VSSN=9 bytes, assume the record pointer size PR=6 bytes. Then:index entry size RI=(VSSN+ PR)=(9+6)=15 bytesindex blocking factor BfrI= B div RI= 1024 div 15= 68 entries/blocknumber of index blocks b= (r/ BfrI)= (3000/68)= 45 blocksbinary search needs log2bI= log245= 6 block accesses + 1This is compared to an average linear search cost of:(b/2)= 3000/2= 1500 block accessesIf the file records are ordered, the binary search cost would be:log2b= log23000= 12 block accessesCopyright © 2011 Ramez Elmasri and Shamkant NavatheTypes of Single-Level IndexesClustering IndexDefined on an ordered data fileThe 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.Includes one index entry for each distinct value of the field; the index entry points to the first data block that contains records with that field value.It is another example of nondense index where Insertion and Deletion is relatively straightforward with a clustering index.Copyright © 2011 Ramez Elmasri and Shamkant NavatheA Clustering Index ExampleCopyright © 2011 Ramez Elmasri and Shamkant NavatheAnother Clustering Index ExampleCopyright © 2011 Ramez Elmasri and Shamkant NavatheTypes of Single-Level IndexesSecondary IndexA secondary index provides a secondary means of accessing a file for which some primary access already exists.The secondary index may be on a field which is a candidate key and has a unique value in every record, or a non-key with duplicate values.The index is an ordered file with two fields.The first field is of the same data type as some non-ordering field of the data file that is an indexing field. The second field is either a block pointer or a record pointer.There can be many secondary indexes (and hence, indexing fields) for the same file.Includes one entry for each record in the data file; hence, it is a dense indexCopyright © 2011 Ramez Elmasri and Shamkant NavatheExample of a Dense Secondary IndexCopyright © 2011 Ramez Elmasri and Shamkant NavatheExample of a Secondary IndexCopyright © 2011 Ramez Elmasri and Shamkant NavatheMulti-Level Indexes Because a single-level index is an ordered file, we can create a primary index to the index itself;In this case, the original index file is called the first-level index and the index to the index is called the second-level index.We can repeat the process, creating a third, fourth, ..., top level until all entries of the top level fit in one disk blockA multi-level index can be created for any type of first-level index (primary, secondary, clustering) as long as the first-level index consists of more than one disk blockCopyright © 2011 Ramez Elmasri and Shamkant NavatheA Two-Level Primary IndexCopyright © 2011 Ramez Elmasri and Shamkant NavatheMulti-Level Indexes Such a multi-level index is a form of search treeHowever, insertion and deletion of new index entries is a severe problem because every level of the index is an ordered file.Copyright © 2011 Ramez Elmasri and Shamkant NavatheA Node in a Search Tree with Pointers to Subtrees Below ItCopyright © 2011 Ramez Elmasri and Shamkant NavatheCopyright © 2011 Ramez Elmasri and Shamkant NavatheDynamic Multilevel Indexes Using B-Trees and B+-TreesMost multi-level indexes use B-tree or B+-tree data structures because of the insertion and deletion problemThis leaves space in each tree node (disk block) to allow for new index entriesThese data structures are variations of search trees that allow efficient
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