Geek Sync | The Universe of Oracle Indexing
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The document discusses various indexing strategies and types available in Oracle databases, emphasizing the importance of understanding and applying the correct indexing options. It covers common index types such as B-tree, bitmap, function-based, and index-organized tables, alongside advanced topics like partitioning and invisible indexes. Presenters will explore best practices for utilizing these indexing methods to enhance database performance and management.
Geek Sync | The Universe of Oracle Indexing
- 1. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level The Universe of Oracle Indexing October 25th, 2017
- 2. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Abstract 2 The Oracle database offers many different types of indexing strategies and thus index types. Today's Oracle DBA needs to be aware of all such indexing options and when each might make sense to apply. Join IDERA and Bert Scalzo as he explores Oracle Indexing. This session will cover every common Oracle index type, including: b-tree, bitmap, bitmap join, reverse order, function based, invisible, partitioned, global prefix, local prefix and index organized tables (IOT's). It's very likely that you are only taking advantage of a small subset of these index types. This is a special Geek Sync you will not want to miss!
- 3. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Presenter 3
- 4. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Agenda Indexing and partitioning What is an index? Many indexing options How indexes are used 3 1 2 4 4
- 5. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level What is an index (conceptually) Traditional definition: • Wikipedia: A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and extra storage space to maintain the index data structure. • Oracle Docs: An index is an optional structure, associated with a table or table cluster, that can sometimes speed data access. Indexes are schema objects that are logically and physically independent of the data in the objects with which they are associated. Thus, you can drop or create an index without physically affecting the indexed table. 5
- 6. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level What is an index (commonly) B-tree index: • Wikipedia: In computer science, a B-tree is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children. • Oracle Docs: B-trees, short for balanced trees, are the most common type of database index. A B-tree index is an ordered list of values divided into ranges. By associating a key with a row or range of rows, B-trees provide excellent retrieval performance for a wide range of queries, including exact match and range searches. 6
- 7. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level What is an index (commonly) 7 Fetch row where col1 = 222 col1 col2 col3 col4 222 X Y Z TABLE
- 8. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level But that is not all … 8
- 9. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level B-tree index options 9 • Unique or not unique • Ascending or descending • Single column or multi column (composite) • Reverse Key (can help with some RAC leaf block contention issues) • Reverse key index is a type of B-tree index that physically reverses the bytes of each index key while keeping the column order. For example, if the index key is 20, and if the two bytes stored for this key in hexadecimal are C1,15 in a standard B-tree index, then a reverse key index stores the bytes as 15,C1. • Compressed (repeated key values removed) • Prefix compression (also known as key compression) to compress portions of the primary key column values in a B-tree index or an index-organized table. Prefix compression can greatly reduce the space consumed by the index. • Starting with Oracle 12c advanced index compression improves on traditional prefix compression for indexes on heap-organized tables. Unlike prefix compression, which uses fixed duplicate key elimination for every block, advanced compression uses adaptive duplicate key elimination on a per-block basis.
- 10. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Bitmap indexes 10 • Database stores a bitmap for each index key. • A mapping function converts each bit in the bitmap to a rowid. • In a conventional B-tree index, one index entry points to a single row. In a bitmap index, each index key stores pointers to multiple rows. • Bitmap indexes are primarily designed for data warehousing or environments in which queries reference many columns in an ad hoc fashion. • Situations that may call for a bitmap index include: • The indexed columns have low cardinality, that is, the number of distinct values is small compared to the number of table rows. • The indexed table is either read-only or not subject to significant modification by DML statements.
- 11. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level How bitmap indexes work Fetch row where color = green Mapping Function 11
- 12. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Bitmap join indexes 12 • A bitmap join index is a bitmap index for the join of two or more tables. For each value in a table column, the index stores the rowid of the corresponding row in the indexed table. In contrast, a standard bitmap index is created on a single table. • A bitmap join index is an efficient means of reducing the volume of data that must be joined by performing restrictions in advance. • Redbrick database (Ralph Kimball) pioneered this and called it “Star Join”
- 13. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level How bitmap join indexes work 13 Fetch row where Fact.col1 = X Dim1.col2 = Y Dim2.col3 = Z Index stores rowid for each table in the join
- 14. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Function based indexes 14 • Function-based indexes are efficient for evaluating statements that contain functions in their WHERE clauses. • The database only uses the function-based index when the function is included in a query. • When the database processes INSERT and UPDATE statements, however, it must still evaluate the function to process the statement. • A function-based index is also useful for indexing only specific rows in a table. For example, the cust_valid column in the sh.customers table has either I or A as a value. To index only the A rows, you could write a function that returns a null value for any rows other than the A rows.
- 15. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Index organized table (IOT) 15 • An index-organized table is a table stored in a variation of a B-tree index structure. • Rows are stored in an index defined on the primary key for the table. • Each index entry in the B-tree also stores the non-key column values. • You can also specify a separate segment as a row overflow area. • Thus, the index is the data, and the data is the index. • If a row overflow area is specified, then the database can divide a row in an index-organized table into the following parts: • The index entry: This part contains column values for all the primary key columns, a physical rowid that points to the overflow part of the row, and optionally a few of the non- key columns. This part is stored in the index segment. • The overflow part: This part contains column values for the remaining non-key columns. This part is stored in the overflow storage area segment.
- 16. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level How IOTs work Branch nodes Leaf nodes Overflow area 16
- 17. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level IOT secondary indexes 17 • A secondary index is an index on an index-organized table. In a sense, it is an index on an index. • The secondary index is an independent schema object and is stored separately from the index-organized table. • A secondary index on an index-organized table can be a bitmap index.
- 18. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Invisible indexes 18 • An invisible index is maintained by DML operations, but is not used by default by the optimizer. • Making an index invisible is an alternative to making it unusable or dropping it. • Invisible indexes are especially useful for testing the removal of an index before dropping it or using indexes temporarily without affecting the overall application.
- 19. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level How invisible indexes work 19
- 20. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Confused yet? There’s more! 20
- 21. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Partitioning objects 21 • Partitioning enables you to decompose very large tables and indexes into smaller and more manageable pieces called partitions. • Each partition is an independent object with its own name and optionally its own storage characteristics.
- 22. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Horizontal partitioning 22
- 23. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Vertical partitioning 23
- 24. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Partitioning benefits 24 • Increased availability • The unavailability of a partition does not entail the unavailability of the object. The query optimizer automatically removes unreferenced partitions from the query plan so queries are not affected when the partitions are unavailable. • Easier administration of schema objects • A partitioned object has pieces that can be managed either collectively or individually. DDL statements can manipulate partitions rather than entire tables or indexes. Thus, you can break up resource-intensive tasks such as rebuilding an index or table. For example, you can move one table partition at a time. If a problem occurs, then only the partition move must be redone, not the table move. Also, dropping a partition avoids executing numerous DELETE statements. • Reduced contention for shared resources in OLTP systems • In some OLTP systems, partitions can decrease contention for a shared resource. For example, DML is distributed over many segments rather than one segment. • Enhanced query performance in data warehouses • In a data warehouse, partitioning can speed processing of ad hoc queries. For example, a sales table containing a million rows can be partitioned by quarter.
- 25. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Basic partitioning 25
- 26. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Extended partitioning 26
- 27. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Indexing under partitioning 27 • Local • (1) Local partitioned index: the index is partitioned on the same columns, with the same number of partitions and the same partition bounds as its table. • (2) Local prefixed index: the partition keys are on the leading edge of the index definition. • (3) Local nonprefixed index: the partition keys are not on the leading edge of the indexed column list and need not be in the list at all. • Global • (4) Global partitioned index: that is partitioned independently of the underlying table on which it is created.
- 28. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level It’s very complicated 28
- 29. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Use indexes judiciously 29
- 30. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level How indexes are used 30 • B-tree • Index Unique Scan • Index Range Scan • Index Full can • Index Fast Full Scan • Index Skip Scan • Index Join Scan • Bitmap • Bitmap Index Single Value • Bitmap Index Range Scan • Bitmap Merge • Bitmap Index Range Scan Too complex to explain today, look for a future webcast on query tuning – indexes vs. exec plans Oracle® Database SQL Tuning Guide 12c Release 1 (12.1) – Chapter 8
- 31. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Index usage summary 31
- 32. Topics Click to edit Master text styles • Second level • Third level − Fourth level • Fifth level Right Choice Greatly Matters 32
- 33. Thank you! • Bert Scalzo – [email protected] – community.idera.com/members/bscalzo/blogs • http://community.idera.com 33