Home Database Oracle Detailed explanation of Oracle database statistical information method

Detailed explanation of Oracle database statistical information method

Apr 11, 2025 pm 05:45 PM
oracle

Oracle database statistics are metadata that optimizes query performance, and its collection methods include automatically collecting benchmark statistics and manually using the ANALYZE command. Statistics cover column data distribution, table data distribution, and index usage. The optimizer uses statistical information to determine the query execution plan, and uses histogram to estimate the number of result rows and predicate push to reduce the number of data reads. It is recommended to update statistics regularly, collect more detailed information for common tables, and monitor their collection and usage to ensure optimal performance.

Detailed explanation of Oracle database statistical information method

Detailed explanation of Oracle database statistical information method

What is statistics?

Oracle database statistics are metadata information about the data distribution and characteristics of database tables and columns, used to optimize query performance.

Methods for collecting statistical information

1. Automatic collection

  • Oracle periodically collects statistics on tables and indexes, called benchmark statistics.
  • The type of statistics collected depends on the size of the table and the frequency of change.

2. Manual collection

  • Use the ANALYZE command to manually collect statistics for specific tables or indexes.
  • This method provides more comprehensive statistics but requires manual intervention from a database administrator (DBA).

Statistical information type

  • Column statistics: Information about the distribution of column data, such as the number of unique values, average length, and missing values ​​ratio.
  • Table statistics: Information about the distribution of table data, such as the number of rows, blocks, and data size.
  • Index statistics: Information about index usage and distribution, such as coverage, cardinality, and selectivity.

How to optimize query performance in statistics

  • Query Optimizer: Use statistics to determine the most efficient query execution plan.
  • Histogram: Stores summary information of column value distribution, used to estimate the number of rows of query results.
  • Predicate push: allows the predicate to be pushed from query to index scan, reducing the amount of data read.

Best Practices

  • Statistics are updated regularly, especially when data changes occur.
  • Collect more detailed statistics for frequently queried tables and indexes.
  • Use the ANALYZE SAMPLE command to collect table samples based statistics to improve efficiency.
  • Monitor statistics collection and usage to ensure optimized performance.

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