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The SQL Optimizer creates optimized execution plans to improve query response time, reduce resource use, and improve user experience.
Developers benefit from this optimization process because it frees them from worrying about low-level query tune-up in favor of designing and developing applications instead.
At the same time, it's also essential to recognize that optimizer decisions don't always produce optimal execution plans.
Execution plans may be affected by factors like uneven data distributions and outdated statistics as well as configurations with suboptimal settings - developers may need to offer suggestions or alter query structures in order to assist the Optimizer with making more optimal choices.
- Query Tuning
- performance tuning tools
- query plan
- query optimizer
Developers should observe best practices to utilize the SQL Optimizer's benefits fully. Effective query optimization requires regular collection of accurate statistics about tables and indexes; using bind variables for plan reuse; considering data distribution effects when allocating plans; carefully designing indexes in order to strike an equilibrium between query speed and maintenance costs - these best practices help developers maximize SQL Optimizer benefits.
Developers have various techniques available to them when the decisions made by an optimizer are sub-optimal. You could adjust session- or system-level parameters, use SQL plan baselines or take an alternate route by switching to "optimizer_mode."
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Oracle SQL Tuning Goals
SQL tuning can be an intricate topic; entire have been dedicated to its complexities. That being said, every Oracle should follow some general guidelines when setting goals for SQL Tuning.
This will maximize system performance.
Oracle SQL Tuning plays an essential role in improving database performance by tuning SQL queries for maximum efficiency of execution and decreased response times.
Ultimately, its aim is to enhance overall database efficiency to handle larger workloads while always remaining responsive.
Search Engine Optimization
Optimizing an SQL query involves writing efficient queries with well-organized structures that only retrieve relevant information, while complex expressions should be avoided as these may create performance issues.
Indexing
Indexing is crucial for retrieving data efficiently. By offering quick access, they accelerate query execution time.
Selecting appropriate indexes reduces the amount of data to scan while improving response time - but over-indexing could result in increased maintenance overhead if too many indexes exist - finding equilibrium is paramount!
Statistics
Oracle SQL optimization relies on accurate statistics to make decisions regarding query execution.
Be sure to update them frequently to enable Oracle's Optimizer to make optimal choices based on current data distribution patterns.
Bind Variables
Bind variables offer another means for creating efficient execution plans without hardcoding the values into queries by enabling databases to reuse an execution plan when processing similar queries despite differences in parameter values, thus reducing the time and effort spent developing new plans.
Caching and Buffering
Oracle's buffer caching allows you to store frequently used data in memory for faster access than using the disk.
Caching can be especially effective for read-intensive workloads where disk access is more time-consuming.
Partitioning
For improved query performance, consider splitting large tables up into more manageable chunks by partitioning them accordingly.
Doing this allows the database to scan only relevant partitions instead of all parts simultaneously.
Visualized Views
Precomputed results sets are materialized views designed to speed up queries significantly by storing results in separate tables to reduce costly calculations.
Rewriting Complex Queries
An analysis of complex queries may uncover ways of writing them more efficiently. An otherwise complex query might be simplified without altering its functionality, providing more efficient performance without losing functionality.
Profile and Monitor
Typically using tools like Oracle's Automatic Workload Repository can assist in regularly monitoring query performance; you may identify poor-performing queries while gaining insights into areas for potential improvement.
Benchmark And Test
Before making changes, assessing their effects thoroughly and measuring performance improvement using realistic workloads is vital.
Benchmarking provides another effective means of tracking tuning success while making informed decisions about it.
Reducing Unnecessary Full-Table Scanning Unnecessary
Full table scans can drain an enormous amount of I/O and significantly slow down a database as their I/O demands become magnified over time.
A tuning expert typically evaluates SQL by inspecting its rows returned by queries; indexes are the most popular solution to prevent full table scans; tables can have standard b-tree, bitmapped or function-based indexes added and full table scans eliminated through adding indexes such as standard b-tree indexes as well; using a hint in SQL query, it's possible to force complete table scanning using an index instead versus forcing full table scanning over time!
- Wide range
- CPU time
- outer query
- Variety of application building
- Application building processes
Cache Full Table And Small Table Scan
When performing full table scans is faster, administrators must ensure a data buffer for every row in the entire table scan is created.
Oracle8 or later allows this by forcing it into the KEEP pool for caching purposes.
Create Aggregations, Summaries and Static Tables
Oracle SQLAccess Advisor provides recommendations and suggestions regarding new indexes. Materialized views provide pre-joining/summarizing tables, making materialized views an excellent solution for databases reporting on data marts where updates occur daily; further reading for materialized view tuning can be found in Oracle Tuning: Definitive reference book.
Here are the main goals of SQL tuning: they may seem straightforward, but to meet them effectively requires an in-depth knowledge of Oracle SQL; to do this, we will begin with an overview of its optimizers.
Oracle Sql Optimizers
Oracle's default optimizer will likely be one of the first things a will examine since its initialization parameters offer multiple cost-based optimization modes and an outdated but helpful rule-based suggestion system.
Cost-based optimizers make decisions using statistics collected through Oracle's analyze table command and used as metrics by Oracle intelligently to service SQL queries most effectively.
While cost-based optimizers continue to improve over time, sometimes rule-based optimizers yield faster Oracle queries.
Before Oracle 10g was introduced, the default Oracle optimizer mode was "choose." In choose mode, rule-based optimization is used if no statistics exist for a table; cost-based optimization takes over when statistics exist, potentially creating issues when only specific tables contain them.
Choose mode can cause issues when one table contains statistics but others do not; an issue arises if only some Oracle tables contain statistics while some do not.
- user-friendly interface
- user interface
- browser level
- Statistics level
- application issues
- Control Center
An Oracle database administrator should begin Oracle tuning by making adjustments to optimizer modes for all queries, starting by changing them all individually and eliminating full table scans as quickly as possible.
An efficient SQL statement consists of statements which need to utilize all available indexes in an Oracle database to speed up their execution and utilize full table scanning rather than all available indexes that could accelerate queries more effectively.
At times a full table scan may be appropriate; for instance, when performing aggregate operations such as totalling or averaging, as most rows in an Oracle table must be read before reading its results.
SQL tuning experts must evaluate each full-table search to see if performance could be enhanced by adding indexes.
Oracle SQL statements typically retrieve only a subset of rows from tables when performing queries against them, using indexes as much as possible to reduce I/O and minimize I/O.
When query formulation is efficient, however, the cost-based Optimizer needs clarification about which access path provides more data - leading it down an inefficient path that could require performing full table scans - something database administrators should always keep an eye out for when reviewing SQL.
Oracle Database Tuning can be daunting for beginners; many need help knowing where to begin when tuning Oracle SQL.
Tuning requires mining the Oracle Library Cache for SQL statements before extracting and tuning them manually. To effectively tune Oracle SQL, this strategy plan for tuning can help.
Step 1: Deliberate Over Potential High-Impact Sql Statements
SQL statements are prioritized according to how often they have been executed and adjusted accordingly. You can use executions columns found within tables
- Processed Rows: Queries which process a high number of rows may have a significant impact on I/O and also the TEMP Tablespace.
- High Buffer Gets: A resource-intensive request may be indicated by a high buffer get.
- High disk reads: A query that causes excessive I/O will likely cause high disk reads.
- Memory Kb: This is useful for identifying SQL statements which perform in-memory joins.
- CPU seconds: This shows the SQL statements which use the highest processor resources.
- Sorts: Sorting can take a long time, mainly if it's done in the TEMP Tablespace.
- Executions: Tuning should begin with the most frequently used SQL statements, which significantly impact performance.
Step 2: Determining The Sql Execution Plan
Every SQL statement will be "explained" to display its current execution plan. Third-party tools may help visualize this execution plan; Oracle often utilizes Oracle's Explain Plan utility for this task - asking it to parse and display an SQL statement before showing its class path without running it!
- Version control
- executable code
- code complexity
- code block
- complex tool
- data-driven tool
- portable tool
Most relational databases use an explain tool, which takes as input a SQL statement, executes its SQL Optimizer and outputs access paths into a table called plan_table that can then be utilized by querying directly for information regarding methods of access.
Step 3: Fine-Tune SQL Statement
An SQL statement with suboptimal execution plans will be fine-tuned using one or more techniques for optimization.
- Add SQL "hints" to the execution plan.
- Use global temporary tables to rewrite the SQL script.
- Rewriting SQL into PL/SQL may increase performance up to 20 times for specific queries by replacing SQL statements with calls into PL/SQL Packages, which contain stored procedures that execute queries directly.
Hints are one of the best tools available for optimizing SQL statements. A hint adds an explicit directive to a statement, altering its path toward producing queries for further examination.
Case Study On Sql Tuning
Formulating queries has long been an issue with SQL servers. There are multiple approaches for writing simple queries; all yield the same result but have different speeds and access methods.
Queries such as, 'Who received an A during this semester?' can be written three different ways, all yielding identical answers.
Read More:SQL and NoSQL solutions to their clients.
They are Both Great but Which One Should You Choose?
Sql Tips To Make Your Code More Efficient
The available space allows us to go into some aspects of Oracle tuning. However, we will share a few general guidelines for creating efficient SQL regardless of which Optimizer is used.
Following these rules diligently will usually solve more than half the SQL tuning issues that you encounter:
- Rewrite complicated subqueries: Oracle developed global temporary tables and the SQL WITH operator to divide and conquer complex SQL subqueries more effectively (especially those featuring WHERE clause scalar queries, FROM clause inline views and SELECT clause subqueries). Tuning SQL using temporary tables and materializations within WITH can improve performance.
- Subqueries with EXISTS are replaced by minus: Some argue that using "minus" in place of NOT IN or NOT Exists produces an execution plan with faster speed.
- Use SQL analytical functions: Oracle's analytic function offers multiple aggregate functions (e.g. Oracle can perform cube roll ups quickly in just one table pass - making reporting SQL queries even faster!). Rollups also happen quickly due to single tables passing rolling data cubes into tables for reporting purposes.
- Convert NOT EXISTS or NOT EXISTS queries to outer joins: Under some conditions, using IS NULL checks could enable you to transform uncorrelated NOT queries into outer joins - although this method would remain non-correlated and could still function effectively as an outer join.
- Create an index for your NULL values: If you frequently test NULL in SQL, consider creating an index to avoid query optimization when testing NULL values for columns (i.e. where emp_name IS NULL, we could use SQL's built-in NULL values function to create an index that indexes only NULL columns).
- Keep column names: Do not perform index column calculations without consulting the function-based (FBI) version. Instead, redesign your schema so predicates in common clauses do not need transformation by BIFs.
- Do not use NOT IN or HAVING: A NOT EXISTS query may be faster to run (when applicable).
- Do not use the LIKE predicate: Always substitute "like" for an equal when necessary.
- Do not mix different data types: When using quotations with numeric columns in the WHERE clause, DO NOT include numeric data types like values. When specifying mixed data types as predicates (predicates are predicate conditions that evaluate to true), always include quotation marks in char index columns (and vice versa). Predicates for mixed data types look like this.
- Decode and Case: By using the decode or case functions, you can reduce the amount of time it takes to select a table.
- Refrain from fear of full table scans: Indexes may not always be the optimal solution for OLTP queries, especially if your query returns a significant percentage of table rows. It all depends on various factors like configuration (db_file_multiblock_read_count, db_block_size), parallelism of query execution and number of table/index blocks currently stored in the buffer cache.
What is Oracle Performance Tuning?
Tuning a database refers to administering it to enhance performance, such as optimizing SQL statements or execution plans to complete requests rapidly.
Oracle performance tuning involves optimizing both aspects of administration. When an application interacts with a database, its SQL queries determine the resources required to answer each query.
- Data-DrivenThis tool
- Performance Tool Box
- Cloud Control
- high-load SQL statements
- driving table
Poorly optimized SQL statements force databases to use more resources when retrieving information, ultimately degrading user experience across other applications.
Users often report slow applications to an administrator of a database in large enterprises. Once reported, this administrator attempts to ascertain their cause by hunting down bottlenecks in the database and analyzing code - an often tedious and drawn-out process, as the administrator must first establish what caused an issue before rectifying it.
Monitor Performance Of Oracle Databases - Response Time And Throughput
There are two useful metrics to use when tuning Oracle databases:
- Response Time – How long it takes the database to process a request.
- Throughput of the system- Number of completed processes in a given period.
An application with a high response time provides an inferior user experience. At the same time, low system throughput means it can only accommodate limited tasks briefly.
Before tuning, an administrator should establish what their goals are before tuning.
What constitutes optimal Oracle database optimization depends upon your goals and application of choice. Specific goals, such as fast response time and high Throughput, cannot coexist effectively.
The goal of fast response time may be to speed up individual queries from users while not degrading other workload tasks. Optimize all workload tasks to handle more transactions per second to maximize performance and achieve a high response rate.
- efficient method
- lookup tables
- Database Connectivity
- Oracle Autonomous Database
- Oracle Cloud
- Oracle Enterprise
What type of application one uses can have an enormous effect. If you were running an OLTP app, its performance must efficiently handle large volumes of transactions to be measured effectively.
Suppose your DSS allows users to simultaneously run queries against hundreds or even thousands of records. In that case, its response time will ultimately measure its performance.
Two Types Of Tuning: Proactive Monitoring And Bottleneck Elimination
After you've learned what performance tuning means, let's look at two of the most common tuning models:
- Monitoring
- Bottleneck Elimination
Database administrators use these two models to ensure applications run at high levels while mitigating performance issues.
Monitoring
Proactive database monitoring enables administrators to detect and solve performance issues before they become issues, rather than waiting until there's already been damage done to detect signs of degradation in real-time.
They should review databases regularly to detect early warning signals of performance decline. Proactive monitoring allows database administrators to spot potential problems before they become more serious, helping prevent potential disruptions to services from emerging as more severe issues.
They keep an eye out for:
- Wait Events in Databases- Performance degradation could occur if the number of wait events exceeds acceptable thresholds. To mitigate performance problems and degradation effectively, sessions that create obstruction should be identified and terminated accordingly.
- Load Average- It is essential to monitor the server's average load average to assess if it's functioning normally and avoid slow database performance, as high load averages may indicate issues on its part.
- Database Sessions- To prevent yourself from exceeding the maximum allowed sessions and inadvertently closing any new ones, limit yourself by staying within this number.
Monitoring proactively can involve certain risks; any change administrators could decrease database performance and bring unexpected effects.
Administrators can minimize this potential danger and mitigate its consequences by being cautious before making any modifications.
Bottleneck Elimination
One of the leading causes of performance issues is bottlenecks. Bottlenecks prevent requests from reaching their destinations and increase application response times; many factors, including poorly coded SQL and excessive resource usage, can contribute to bottleneck formation.
Elimination of bottlenecks is more reactive than proactive. An administrator usually detects bottlenecks before fixing them; fixing processes vary depending on whether a cause (internal or external).
One solution for internal bottlenecks is recoding SQL statements. Once internal bottlenecks have been resolved, an administrator should investigate other potential factors, including CPU performance and storage, which might contribute to issues.
They can alter Oracle configuration, hardware components or even applications as necessary to remedy them.
A Guide to Tuning Performance
Oracle performance tuning can be challenging due to all the variables influencing it. We will keep things straightforward by exploring some basic methods you can employ in order to optimize its performance.
Determine Which Queries Are Expensive
To effectively tune SQL code, the initial step must be identifying high-cost queries and resource requirements. Rather than optimizing every line of code individually, focus on optimizing those most frequently used and having an extensive I/O footprint, as these will likely yield the most significant returns in performance gains.
Oracle monitoring tools efficiently pinpoint which queries cost the most money (we will discuss some platforms later on).
Oracle SQL Analyze provides another valuable method of finding statements with high resource requirements so you can optimize these SQL statements to get maximum return for investment.
Index Your Data To Decrease The Workload
It can be advantageous to write code that minimizes work. Processing hundreds or even thousands of rows unneeded when only interested in snapshots would only waste resources and require extra I/O operations from your database server.
Indexes can help reduce workload and stress when querying one column multiple times; indexes are particularly effective. They're convenient in cases when this column is often queried upon.
Integrate Applications With Stateful Services
Sometimes the cause of poor performance lies beyond the code itself - sometimes, the issue could lie with how frequently applications connect and disconnect from databases; your app could connect briefly when retrieving table data but then drop out again once all its records have been downloaded.
Once your application accesses a table, maintaining an active connection should help to improve performance. By maintaining it continuously, system resources will be well-spent every time an interaction occurs with the database.
Use Optimizer To Collect And Store Statistics
The Optimizer helps a database gather statistics which describe its objects, users and data that is then used by it in determining optimal execution plans of SQL statements.
Therefore, we must collect and store Optimizer statistics regularly across database objects to maintain efficiency.
By collecting optimizer statistics, you can ensure your database has accurate information regarding table content.
Otherwise, an accurate execution plan might be selected, affecting user experiences positively.
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Conclusion
Oracle Database Development requires an Optimizer as part of its strategy for efficient query execution.
It provides optimal plans based on variables like table statistics, indexes and available resources for optimal plan generation that reduce execution times as much as possible. The Optimizer also analyzes table statistics, such as table membership, to optimize query execution performance by finding ways to leverage timesaving tactics such as caching.
The SQL Optimizer plays an essential part in improving Oracle Database performance, using sophisticated algorithms to select optimal execution plans that improve query response time and reduce resource consumption.
Developers should maintain up-to-date statistics, create effective indexes, and utilize hint capabilities when necessary to help guide and direct the Optimizer when necessary. Likewise, periodic review plans must be evaluated to maintain optimal performance over time as user and data volumes fluctuate.
