How Do You Gather Stats for a Table in Oracle?
In the world of database management, ensuring optimal query performance is a constant challenge. One of the foundational steps toward achieving this in Oracle databases is the process of gathering statistics for tables. These statistics serve as vital insights that the Oracle optimizer relies on to devise the most efficient execution plans. Without accurate and up-to-date statistics, even well-designed queries can suffer from sluggish performance and resource inefficiencies.
Gathering statistics for tables in Oracle is more than just a routine maintenance task; it’s a strategic activity that directly impacts how data retrieval operations are executed. By analyzing data distribution, table size, and index information, the optimizer can make informed decisions that reduce response times and improve overall system throughput. As data evolves and grows, the importance of refreshing these statistics cannot be overstated, making this process an essential part of database tuning and administration.
This article will explore the significance of stats gathering for tables in Oracle, shedding light on why it matters and how it influences performance. Whether you’re a DBA aiming to enhance system efficiency or a developer seeking to understand the inner workings of query optimization, understanding this topic is key to mastering Oracle database performance.
Methods to Gather Statistics for a Table
Gathering statistics in Oracle is essential for the optimizer to make informed decisions about query execution plans. Oracle provides multiple methods to collect these statistics, each suitable for different scenarios depending on data size, update frequency, and system workload.
The primary methods to gather statistics include:
- DBMS_STATS Package: The preferred and most flexible method, offering a wide range of options to collect statistics at various levels such as table, schema, or database. It supports gathering statistics concurrently and supports incremental statistics for partitioned tables.
- ANALYZE Command: An older method used primarily for backward compatibility. It can gather statistics and validate tables but is generally discouraged in favor of DBMS_STATS due to limitations and lack of ongoing support.
- Automatic Statistics Gathering: Oracle has a built-in job that runs during maintenance windows to automatically gather statistics for objects that require it, based on stale or missing statistics.
Each method has specific parameters and behaviors that affect how statistics are collected and refreshed.
Using DBMS_STATS to Gather Table Statistics
The `DBMS_STATS` package is the recommended approach for gathering optimizer statistics. It provides granular control over the statistics collection process, including options for sampling, parallel execution, and statistics locking.
A typical call to gather statistics for a table looks like this:
“`sql
EXEC DBMS_STATS.GATHER_TABLE_STATS(
ownname => ‘SCHEMA_NAME’,
tabname => ‘TABLE_NAME’,
estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
method_opt => ‘FOR ALL COLUMNS SIZE AUTO’,
cascade => TRUE,
degree => 4
);
“`
Key parameters:
- `ownname`: Specifies the schema owner of the table.
- `tabname`: The name of the table to analyze.
- `estimate_percent`: Determines the sample size. Using `AUTO_SAMPLE_SIZE` lets Oracle decide the optimal percentage.
- `method_opt`: Defines how column statistics are gathered; `FOR ALL COLUMNS SIZE AUTO` collects histograms automatically where needed.
- `cascade`: If set to `TRUE`, gathers statistics on indexes related to the table.
- `degree`: Controls the degree of parallelism for the operation.
Understanding Statistics Components
Statistics consist of various components that provide detailed information about the data distribution and storage characteristics. These components influence the optimizer’s cost calculations and plan generation.
Important statistics components include:
- Table-level statistics: Number of rows, blocks, empty blocks, average row length.
- Column-level statistics: Number of distinct values (NDV), number of nulls, data distribution, histograms.
- Index statistics: Number of leaf blocks, clustering factor, height.
Oracle allows gathering these components selectively by using the `granularity` and `stattab` parameters or by specifying particular columns or indexes.
Comparing Statistics Gathering Options
Choosing the right options when gathering statistics can impact both the accuracy of the optimizer’s decisions and the time taken to collect the statistics. Below is a comparison of common options used in `DBMS_STATS.GATHER_TABLE_STATS`:
| Option | Description | Use Case |
|---|---|---|
| estimate_percent | Defines the percentage of rows to sample for statistics. | Use AUTO_SAMPLE_SIZE for automatic tuning; specify a fixed value for control. |
| method_opt | Controls collection of column statistics and histograms. | Use ‘FOR ALL COLUMNS SIZE AUTO’ for adaptive histogram creation. |
| cascade | Determines whether to gather stats on indexes. | Set TRUE to include indexes; to exclude them. |
| degree | Specifies parallelism level for stats gathering. | Increase for large tables to reduce execution time. |
| granularity | Defines the level of detail (e.g., ALL, PARTITION, SUBPARTITION). | Use PARTITION for partitioned tables to gather stats per partition. |
Incremental Statistics Gathering for Partitioned Tables
For large partitioned tables, gathering statistics on the entire table can be resource-intensive. Oracle supports incremental statistics gathering that allows collecting statistics on individual partitions and then merging them to form global statistics.
To enable incremental statistics:
- Set the table property `INCREMENTAL` to `TRUE` using `DBMS_STATS.SET_TABLE_PREFS`.
- Gather statistics on partitions as they change.
- Oracle automatically merges partition statistics into global statistics.
Example:
“`sql
EXEC DBMS_STATS.SET_TABLE_PREFS(
ownname => ‘SCHEMA_NAME’,
tabname => ‘PARTITIONED_TABLE’,
pname => ‘INCREMENTAL’,
pvalue => ‘TRUE’
);
EXEC DBMS_STATS.GATHER_TABLE_STATS(
ownname => ‘SCHEMA_NAME’,
tabname => ‘PARTITIONED_TABLE’,
granularity => ‘PARTITION’
);
“`
This approach reduces the time and system load required for statistics gathering while maintaining optimizer accuracy for partitioned data.
Understanding Statistics Gathering for Tables in Oracle
In Oracle Database, gathering statistics on tables is essential for the cost-based optimizer (CBO) to generate efficient execution plans. Accurate and up-to-date statistics enable Oracle to estimate cardinality, selectivity, and data distribution effectively.
Statistics gathering involves collecting metadata such as:
- Number of rows in the table
- Number of distinct values (NDV) for columns
- Data distribution histograms
- Table and index size
- Number of blocks and empty blocks
These statistics are stored in the data dictionary and influence SQL execution plans.
Methods to Gather Statistics on Tables
Oracle offers several methods to gather statistics, each suited to different scenarios:
- DBMS_STATS Package: The recommended and most flexible method for gathering statistics.
- ANALYZE TABLE Statement: Legacy command, now deprecated for statistics gathering.
- Automatic Statistics Gathering: Oracle’s automated job that runs during maintenance windows.
Using DBMS_STATS to Gather Table Statistics
The DBMS_STATS package provides procedures to gather, delete, and lock statistics. The primary procedure is GATHER_TABLE_STATS.
Example syntax:
“`sql
BEGIN
DBMS_STATS.GATHER_TABLE_STATS(
ownname => ‘HR’,
tabname => ‘EMPLOYEES’,
estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
method_opt => ‘FOR ALL COLUMNS SIZE AUTO’,
cascade => TRUE,
degree => 4
);
END;
/
“`
Key parameters:
| Parameter | Description |
|---|---|
| ownname | Schema name of the table |
| tabname | Table name |
| estimate_percent | Percentage of rows to sample (default is AUTO_SAMPLE_SIZE) |
| method_opt | Controls column statistics, histograms (e.g., ‘FOR ALL COLUMNS SIZE AUTO’) |
| cascade | If TRUE, gathers index statistics as well |
| degree | Degree of parallelism for gathering statistics |
Best Practices for Using DBMS_STATS
- Use
estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZEfor adaptive sampling. - Set
method_optto create histograms only on columns that require them, typically withSIZE AUTO. - Gather statistics during low-load periods to minimize performance impact.
- Use
cascade => TRUEto update statistics on indexes related to the table. - Lock statistics with
DBMS_STATS.LOCK_TABLE_STATSif you want to prevent automatic changes.
Automatic Statistics Gathering in Oracle
Oracle Database includes an automatic statistics gathering job that runs during maintenance windows, typically at night. It targets tables and partitions that require statistics refresh based on change thresholds.
Key features:
- Uses incremental statistics for partitioned tables (if enabled).
- Automatically decides which objects need statistics based on stale or missing stats.
- Respects locked statistics and does not overwrite them.
- Can be customized or disabled using database preferences.
Viewing and Managing Table Statistics
Statistics for tables and columns can be viewed via data dictionary views:
| View | Description |
|---|---|
DBA_TAB_STATISTICS |
Statistics for tables, including row counts, blocks, and stale flags. |
DBA_TAB_COL_STATISTICS |
Column-level statistics such as NDV, histograms, and null counts. |
DBA_IND_STATISTICS |
Statistics for indexes, including leaf blocks and distinct keys. |
To check if statistics are stale:
“`sql
SELECT table_name, stale_stats
FROM dba_tab_statistics
WHERE owner = ‘HR’;
“`
A value of ‘YES’ indicates stale statistics that may require gathering.
Controlling Statistics Gathering Behavior
Oracle provides various parameters and preferences via DBMS_STATS to fine-tune statistics collection:
- Stale Statistics Threshold: Controls when stats are considered stale (default 10% change).
- Incremental Statistics: Improves performance for partitioned tables by gathering stats only on changed partitions.
- Global Stats Locking: Prevents automatic statistics refresh for critical tables.
- Parallelism: Use the
degreeparameter to speed up statistics gathering. - Estimate Percent: Sampling size to balance accuracy and performance.
Example of setting a preference for stale percent:
“`sql
BEGIN
DBMS_STATS.SET_DATABASE_PREFS(‘STALE_PERCENT’, ’20’);
END;
/
“`
This changes the threshold for considering statistics stale to 20%.
Impact of Accurate Statistics on Query Performance
Accurate statistics enable the optimizer to choose optimal access paths, join methods, and parallelism. Without them, the optimizer might:
- Choose full table scans over indexes or vice versa incorrectly.
- Underestimate or overestimate row counts, leading to inefficient joins.
- Generate suboptimal execution plans causing slow query performance.
Therefore, regularly gathering and maintaining table statistics is critical in Oracle database performance tuning and management.