stats gather for table in oracle

asalmes

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04-12-2024

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Oracle's performance heavily relies on accurate statistics. Without up-to-date statistics, the query optimizer may choose inefficient execution plans, leading to slow query performance. This article provides a comprehensive guide on gathering statistics for tables in Oracle. We'll cover various methods, best practices, and troubleshooting tips.

Understanding Oracle Statistics

Before diving into how to gather statistics, let's understand what they are. Oracle's query optimizer uses statistics to estimate the cost of different execution plans. These statistics include:

• Number of rows: The total number of rows in the table.
• Column histograms: Distributions of data values within each column. These histograms help the optimizer estimate selectivity (how many rows will match a specific WHERE clause condition).
• Index statistics: Statistics on the indexes associated with the table, such as the number of leaf blocks and unique index entries.

Accurate statistics are crucial for optimal query performance. Outdated statistics can lead to:

• Poor query plans: The optimizer might choose a suboptimal plan, resulting in slow query execution.
• Increased resource consumption: Inefficient plans consume more CPU, memory, and I/O resources.
• Unpredictable performance: Query performance can fluctuate unpredictably due to inaccurate estimations.

Methods for Gathering Statistics

Oracle offers several ways to gather statistics, each with its strengths and weaknesses:

1. DBMS_STATS Package

The DBMS_STATS package is the primary and most flexible method. It allows fine-grained control over the statistics gathering process.

Basic Statistics Gathering:

EXEC DBMS_STATS.GATHER_TABLE_STATS(ownname => 'YOUR_SCHEMA', tabname => 'YOUR_TABLE');

Replace YOUR_SCHEMA and YOUR_TABLE with the appropriate schema and table names. This command gathers basic statistics, including row counts and column histograms.

Advanced Options:

The DBMS_STATS.GATHER_TABLE_STATS procedure offers many parameters for customizing the statistics gathering process. These include:

• cascade => TRUE: Gathers statistics for indexes associated with the table.
• method_opt => 'FOR ALL COLUMNS SIZE 1' : Controls the histogram size. Larger histograms provide more accuracy but consume more space and time.
• estimate_percent => 10: Specifies a sample percentage for large tables to improve performance.

2. Automatic Statistics Gathering

Oracle can automatically gather statistics for tables using the AUTO_SAMPLE_SIZE initialization parameter and the job DBMS_JOB.SUBMIT. You can configure this in your initialization parameter file. Automatic gathering provides a convenient way to keep statistics updated but might not always be ideal for all tables.

3. ANALYZE Command

The ANALYZE command is a simpler method for gathering statistics. However, it offers less control than DBMS_STATS.

ANALYZE TABLE YOUR_TABLE COMPUTE STATISTICS;

This command gathers basic statistics for the table.

Best Practices for Statistics Gathering

• Gather statistics regularly: For frequently updated tables, gather statistics more often (e.g., daily or weekly). For infrequently updated tables, less frequent gathering might suffice.
• Consider table size: For very large tables, use estimate_percent to sample a portion of the data.
• Use appropriate histogram sizes: Choose histogram sizes based on data distribution and query patterns.
• Monitor performance: After gathering statistics, monitor query performance to ensure improvements.
• Gather statistics after major DDL changes: Always gather statistics after significant changes, such as adding or dropping columns, or creating/dropping indexes.

Troubleshooting Statistics Issues

If you experience performance problems despite gathering statistics, consider the following:

• Check for outdated statistics: Use DBMS_STATS.GET_STATS to verify the last time statistics were gathered.
• Review execution plans: Use EXPLAIN PLAN to examine the query execution plan and identify potential inefficiencies.
• Analyze data distribution: Understanding your data distribution can help determine the appropriate histogram sizes.
• Consider using database monitoring tools: These tools can provide insights into query performance and potential bottlenecks.

Conclusion

Gathering accurate statistics is vital for optimal Oracle database performance. By using the methods and best practices described in this guide, you can ensure your query optimizer is making informed decisions, leading to faster and more efficient query execution. Remember to regularly review and adjust your statistics gathering strategy based on your specific database workload and performance requirements. Proactive management of statistics will contribute significantly to a healthy and performant Oracle database.