table stats gather in oracle

Lemon

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03-02-2025

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Gathering accurate table statistics is crucial for Oracle database performance. Without up-to-date statistics, the query optimizer may generate suboptimal execution plans, leading to slow query performance and impacting the overall database efficiency. This comprehensive guide explores the intricacies of Oracle table statistics gathering, covering various methods, best practices, and troubleshooting techniques.

What are Oracle Table Statistics?

Oracle database statistics are metadata describing the contents of tables, indexes, and partitions. These statistics include information such as:

• Number of rows: The total number of rows in a table or partition.
• Column data distribution: Histograms showing the frequency distribution of values for each column. This is crucial for the optimizer to understand data selectivity.
• Index statistics: Information about the size and structure of indexes, including the number of leaf blocks and the distribution of key values.
• Partition statistics: Statistics for individual partitions of a partitioned table.

The query optimizer utilizes these statistics to estimate the cost of different query execution plans and choose the most efficient one. Inaccurate or outdated statistics can lead to poor plan choices and significant performance degradation.

Methods for Gathering Table Statistics

Oracle provides several ways to gather table statistics:

1. DBMS_STATS Package

The DBMS_STATS package is the primary tool for managing statistics. It offers various procedures for gathering, deleting, and analyzing statistics. Key procedures include:

• gather_table_stats: Gathers statistics for a specific table or partition. This allows for granular control over which tables or partitions require updated statistics. You can specify options like method_opt, cascade, and estimate_percent.
• gather_database_stats: Gathers statistics for the entire database. This is typically used for initial statistics gathering or periodic database-wide updates. Avoid running this during peak hours due to potential resource contention.
• gather_schema_stats: Gathers statistics for all tables and indexes within a specific schema. This is a convenient option for schema-level updates.
• delete_table_stats: Deletes existing statistics for a specific table or partition, often used before re-gathering to ensure fresh data.

Example using gather_table_stats:

EXEC DBMS_STATS.GATHER_TABLE_STATS(
  ownname => 'YOUR_SCHEMA_NAME',
  tabname => 'YOUR_TABLE_NAME',
  estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
  method_opt => 'FOR ALL COLUMNS SIZE 1'
);

Replace YOUR_SCHEMA_NAME and YOUR_TABLE_NAME with your schema and table names. estimate_percent controls sampling; DBMS_STATS.AUTO_SAMPLE_SIZE lets Oracle decide. method_opt controls histogram creation.

2. Automatic Statistics Gathering

Oracle's automatic statistics gathering feature periodically updates statistics based on a schedule defined in the initialization parameter AUTO_STATS. This minimizes manual intervention but might not be sufficient for frequently changing tables.

3. Using ANALYZE Command

The ANALYZE command offers a simpler way to gather statistics, but it offers less granular control than DBMS_STATS.

Example:

ANALYZE TABLE YOUR_TABLE_NAME COMPUTE STATISTICS;

Best Practices for Statistics Gathering

• Frequency: Regularly gather statistics for frequently updated tables. The frequency depends on the data volatility.
• Sampling: Use sampling (estimate_percent) for large tables to reduce the time required for statistics gathering, but balance accuracy against performance.
• Method Options: Experiment with method_opt to find the optimal histogram settings for your data. Incorrect histogram choices can lead to sub-optimal query plans.
• Monitoring: Monitor query performance and execution plans to identify potential issues related to outdated statistics.
• Partitioning: For partitioned tables, gather statistics at the partition level for better accuracy.
• Avoid Peak Hours: Schedule statistics gathering during off-peak hours to minimize impact on application performance.

Troubleshooting Poor Statistics

If you suspect outdated statistics are causing performance issues, follow these steps:

1. Check Last Analyzed Time: Use DBA_TAB_STATISTICS to find the last time statistics were gathered.
2. Examine Execution Plans: Analyze the query execution plans to identify potential issues caused by inaccurate estimates. Look for full table scans when indexes should be used.
3. Gather Statistics: Regather statistics for affected tables or partitions, using appropriate sampling and method options.
4. Monitor Performance: Track query performance after gathering statistics to confirm improvements.

By following these best practices and troubleshooting steps, you can ensure that your Oracle database consistently utilizes accurate statistics for optimal query performance. Remember to adapt your approach based on your specific database workload and data characteristics.