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Managing Schema Objects

Managing Schema Objects. Table Types Partition IOT Cluster DBA Tasks. Objectives. After completing this lesson, you should be able to manage schema objects and: Determine appropriate table types for your requirements: heap, partition, IOT, or cluster Perform related DBA tasks:

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Managing Schema Objects

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  1. Managing Schema Objects

  2. Table Types Partition IOT Cluster DBA Tasks Objectives • After completing this lesson, you should be able to manage schema objects and: • Determine appropriate table types for your requirements: heap, partition, IOT, or cluster • Perform related DBA tasks: • Estimating the size of new tables • Analyzing growth trends • Managing optimizer statistics • Reorganizing schema objects online

  3. Type Description Ordinary (heap-organized) table Data is stored as an unordered collection (heap). Partitioned table Data is divided into smaller, more manageable pieces. Index-organized table (IOT) Data (including non-key values) is sorted and stored in a B-tree index structure. Clustered table Related data from more than one table are stored together. Table Types Clustered Heap Partitioned IOT

  4. What Is a Partition and Why Use It? Table Types > Partition IOT Cluster DBA Tasks • A partition is: • A piece of a “very large” table or index • Stored in its own segment • Used for improved performance and manageability

  5. Partitions • Characteristics of partitions are: • Same logical attributes: Same columns, constraints, and indexes • Different physical attributes: Stored in different tablespaces • Transparent to applications • Several partitioning methods

  6. Creating a Partition

  7. Partitioning Methods • Range partitioning: Maps rows based on logical ranges of columns values—for example, months in a year • Hash partitioning: Maps rows based on the hash value of the partitioning key • List partitioning: Maps rows based on a discrete list of values, provided by the DBA • Range-hash partitioning: Maps rows using the range method, and within each range partition, creates hash subpartitions • Range-list partitioning: Maps rows first based on a range of values, then based on discrete values

  8. Partition Maintenance

  9. Index-Organized Tables Table Types Partition > IOT Cluster DBA Tasks Regular table access IOT access Table accessby ROWID Non-key columns Key column Row header

  10. Index-Organized Tablesand Heap Tables • Compared to heap tables, IOTs: • Have faster key-based access to table data • Do not duplicate the storage of primary key values • Require less storage • Use secondary indexes and logical row IDs • Have higher availability because table reorganization does not invalidate secondary indexes • IOTs have the following restrictions: • Must have a primary key that is not DEFERRABLE • Cannot be clustered • Cannot use composite partitioning • Cannot contain a column of type ROWID or LONG

  11. Creating Index-Organized Tables SQL> CREATE TABLE country 2 ( country_id CHAR(2) 3 CONSTRAINT country_id_nn NOT NULL, 4 country_name VARCHAR2(40), 5 currency_name VARCHAR2(25), 6 currency_symbol VARCHAR2(3), 7 map BLOB, 8 flag BLOB, 9 CONSTRAINT country_c_id_pk 10 PRIMARY KEY (country_id)) 11 ORGANIZATION INDEX 12 TABLESPACE indx 13 PCTTHRESHOLD 20 14 OVERFLOW TABLESPACE users;

  12. Table Types Partition IOT > Cluster DBA Tasks Clusters Cluster Key (ORD_NO) 101 ORD_DT CUST_CD 05-JAN-97 R01 PROD QTY A4102 20 A5675 19 W0824 10 102 ORD_DT CUST_CD 07-JAN-97 N45 PROD QTY A2091 11 G7830 20 N9587 26 ORD_NO PROD QTY ... ----- ------ ------ 101 A4102 20 102 A2091 11 102 G7830 20 102 N9587 26 101 A5675 19 101 W0824 10 ORD_NO ORD_DT CUST_CD ------ ------ ------ 101 05-JAN-97 R01 102 07-JAN-97 N45 Unclustered orders and order_item tables Clustered orders and order_item tables

  13. 1 2 3 Cluster Types Hash cluster Sorted hash cluster Index cluster Hash function Hash function

  14. Criterion • Index Hash • Sorted hash • Uniform key distribution • Evenly distributed key values • Rarely updated key • Often joined master-detail tables • Predictable number of key values • Queries using equality predicate on key • Data is retrieved in the order it was inserted Situations Where Clusters Are Useful

  15. Sorted Hash Cluster: Overview • New data structure used to store data sorted by nonprimary key columns: • Cluster key values are hashed. • Rows corresponding to a particular cluster key value are sorted according to the sort key. • Used to guarantee that row order is returned by queries without sorting data: • Rows are returned in ascending or descending order for a particular cluster key value. • ORDERBY clause is not mandatory to retrieve rows in ascending order.

  16. Sorted Hash Cluster: Example CREATE CLUSTER calls_cluster ( origin_number NUMBER , call_timestamp NUMBER SORT , call_duration NUMBER SORT) HASHKEYS 10000 SINGLE TABLE HASH IS origin_number SIZE 50; Cluster key Sort key CREATE TABLE calls ( origin_number NUMBER , call_timestamp NUMBER , call_duration NUMBER , other_info VARCHAR2(30)) CLUSTER calls_cluster( origin_number,call_timestamp,call_duration );

  17. Sorted Hash Cluster: Basic Architecture SIZE Cluster key 1 Cluster key 2 Block chainstarting points HASHKEYS … Cluster key n Rows sorted bysort key in eachblock chain …

  18. Schema Management Tasks Table Types Partition IOT Cluster > DBA Tasks • DBA tasks include: • Estimating the size of new tables • Analyzing growth trends • Managing optimizer statistics • Reorganizing schema objects online

  19. Estimating Resource Usage

  20. Analyzing Growth Trends • EM growth trend report: • Used by the Segment Advisor • Space usage statistics collected into AWR

  21. Managing Optimizer Statistics 2 3 1 Not analyzed

  22. Reorganizing Schema Objects Online • Modifying logical or physical structure of a schema object, such as a table or index • Transparent to users • Space requirements

  23. Reorganizing Objects:Impact Report

  24. Reorganizing Objects: Review

  25. Basic Steps for Manual Online Reorganization • Verify that the table is a candidate for online reorganization. • Create an interim table. • Start the redefinition process. • Copy dependent objects. (This automatically creates any triggers, indexes, grants, and constraints on the interim table.) • Query the DBA_REDEFINITION_ERRORS view to check for errors. • Optionally, synchronize the interim table. • Complete the redefinition. • Drop the interim table.

  26. Summary In this lesson, you should have learned how to manage schema objects and: • Determine appropriate table types for your requirements • Perform related DBA tasks: • Estimating the size of new tables • Analyzing growth trends • Managing optimizer statistics • Reorganizing schema objects online

  27. Practice Overview:Managing Schema Objects • This practice covers the following topics: • Monitoring table and index space usage • Managing optimizer statistics • Reorganizing table and index

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