Stored procedures are increasing in popularity in Oracle Database and SQL Server because of quicker execution. Earlier, application code mostly resided in external programs. However, its shift toward database engine interiors compels database professionals to keep their memory requirements in mind.
This is as necessary as planning for times when the code related to database access will be present within the database. They also need to know how they can handle these stored procedures to maintain ideal database performance. We will look at some of these methods and the advantages of using stored procedures and triggers in the Oracle database.
Perks of Stored Procedures for Oracle Database Performance Tuning
Until recently, a majority of Oracle databases had limited code within their stored procedures. This shift in trends is because of the various advantages that come with placing larger amounts of code, such as the following:
Performance Improvement – Using more stored procedures means you don’t require Oracle database performance tuning as much. That’s because each of these only has to load once into the shared pool. Executing them, therefore, is quicker than running external code.
Code Segregation – The stored procedures have all the SQL codes which turn all the application programs into calls for those procedures. This is an improvement in the data retrieval process because changing databases gets simpler.
Therefore, one advantage you get through stored procedures is the ability to transfer large amounts of SQL code to the data dictionary. Doing this will enable you to perform SQL tuning without involving the application layer.
Group Data Easily – You can gather relational tables with data that shares certain behaviour before looking for Oracle performance tuning tips. Simply use Oracle stored procedures as methods, along with suitable naming conventions. For example, link the behaviour of the table data to the table name in the form of prefixes.
The users may then request the data dictionary to display all the traits connected to one table. This makes it more convenient to recognise and reuse code with the help of stored procedures.
Other Reasons Behind the Increasing Popularity of Stored Procedures
There are plenty of other reasons stored procedures and triggers take less time in comparison with conventional code. One of these has something to do with SGA caching in Oracle database and SQL.
Once the shared pool within the SGA gets a hold of a stored procedure, it keeps it there until the procedure gets paged out from the memory. The SGA mostly does this to create space for other stored procedures. The paging out process takes place based on a Least Recently Used or LRU algorithm.
Two parameters help determine the amount of space that Oracle uses on startup. These are the Cache Size and the Shared Pool Size parameters. They also help users check how much storage space is available for various tasks. These include caching SQL code, data blocks, and stored procedures.
Stored procedures will run extremely fast once you load them into the shared pool’s RAM – as long as you can avoid pool thrashing. This is important because several procedures compete for varying quantities of memory in the shared pool.
The performance of an Oracle database and SQL query speed can directly affect the organisation it belongs to. If the queries running in the database are slow, they will surely have a negative impact. However, its severity may vary based on the database’s role, its architecture, and the industry your organisation operates in.
Regardless of the extent, it would be unwise to ignore them, which is why we are going to talk about all their effects in this blog.
How Slow Statements Affect Oracle Database and SQL Users
In this fast-paced world, everything needs to work fast and offer a quick response time to its end-users. The data that a web page displays generally comes directly from the database with very few interactions.
This implies the dependency of the application’s response time on the time it takes for the queries to run and the database to respond. Slow statements will take more time, resulting in loading screens before the desired information shows up. This is when Oracle database performance tuning becomes a requirement.
Such speeds don’t affect only the application, however; they leave an impact on the other parts of a system as well. The reason behind this is the location of the database in a majority of web architectures.
Take a look at the three-tier architecture, for example – the database lies at the bottom in most cases, forming the foundation. An increase in latency here is likely to cause the same in the higher levels along with other areas in the system.
Another way in which slow queries negatively impact the system is by making the database use more resources than is actually necessary. Some of these are available in limited quantities, such as I/O and CPU, since other applications share these resources.
On the other hand, not using existing resources sufficiently leads to their inefficient usage and slow queries as well. This may be the case with your database, so you may want to consider a few Oracle performance tuning tips that deal with this particular issue.
Top Reasons Behind Slow and Inefficient Queries
Given below are the three most significant causes of queries slowing down:
- Too many tasks: Executing a statement includes multiple tasks, such as retrieving data, making calculations, and arranging data in the order as the query specifies. All of these involve plenty of factors, any of which can increase the amount and complexity of work done, from joining and grouping to filtering and sorting.
- Too much waiting: Sometimes, statements don’t have too much to do, nor are they stuck waiting for resources. The reason why they are sluggish is that they are waiting on other statements that are locking resources or requiring higher levels of activity.
- Too few resources: Query execution works alongside other tasks taking place within a system. This means they share resources such as network throughput, disk I/O, and CPU. Statement execution is likely to take more time when these are completely occupied.
Locating and Working on Slow Queries in Oracle Database
Slow queries don’t get faster on their own – DBAs must take steps to speed them up. For starters, they can use the Database Performance Monitor (DPM) in the following ways:
- Viewing all the queries that are taking up execution time using the query profiler. Such queries are often running in the absence of indexes, so it’s a good idea to add one to improve Oracle database performance and execution speed.
- Automatically collecting explain plans to get a quick glance at the ones that contain information regarding slow queries and the changes related to them, if any.
- Assessing Oracle database and SQL to find out whether a statement can perform better with the help of some improvements.
- Visiting the charts page to go through properly arranged metrics pertaining to system performance. This allows the DBA to set a threshold alert and note changes every time a system resource is reaching maximum use.
Based on your architecture and application, slow statements can affect more aspects of your business than just the database. Therefore, ignoring them is not recommended as it often results in a detrimental impact on both end-users and your organisation.
Consider enlisting the help of professional tuning tools to improve slow query performance in Oracle and SQL Server databases.
A lot of database professionals often need to archive older data in SQL Server by transferring it from one table to another. There are multiple ways to achieve the transfer, the most useful of which we will discuss in this blog. We will also provide tips to ensure the performance of the database doesn’t get affected as these approaches are carried out.
Different Methods to Move Data from One Table to Another
Consider the following techniques that various DBAs take when they have to take data from a table to add to another table along with some ways to improve performance of SQL query while using them:
- Insert data with the INSERT INTO command – The INSERT INTO query is one of the basic methods of moving data from table 1 to table 2. You can help decrease the time it takes to enter information using this method. If the database is running under the full recovery model, just change it to the bulk-logged model. Doing this saves execution time as it skips over complete logging of bulk operations. The following query should help with this:
ALTER DATABASE <database name> SET RECOVERY <BULK_LOGGED>
Once you switch to the bulk-logged recovery model, you will have to use a truncate statement to flush table 2 (destination). You can carry out the same script you were using to transfer data after this.
- Use the SELECT INTO query – Using the SELECT INTO rather than the INSERT INTO command can prove useful in some cases. However, the benefits are significant when the recovery model is bulk-logged due to the reason mentioned above. Although users lack the ability to place the data in an existing table, SQL Server brought with it a feature to make things easier. It essentially enables them to pick the filegroup where they want to create a table.
- INSERT INTO query + Tab lock hint – Using both in combination has been known to provide better database performance. To achieve this, you will have to use TABLOCK for table 2. If the destination table is without a clustered index or other constraints, that data will remain as a heap. It helps to use the TABLOCK hint for the destination table during data insertion into a heap using the INSERT INTO statement. Doing this enhances query logging and locking since a shared lock is placed on the whole table rather than every row or page.
- Adding data using the SWITCH TO query – You can also try moving the data with the help of the SWITCH TO command. Although this query typically finds its use while transferring information between partitions among separate tables, it can help here as well. How? By moving data from one partition to the next using the ALTER TABLE command. If there are no allocated partitions, the data will transfer through tables instead. Before you begin data insertion, make sure you disable any constraints or indexes that exist on the table. It is better to enable constraints and rebuild indexes after insertion from a performance perspective.
Tips for Enhancing Performance During Data Transfer and Insertion
- Reduce IO lag – Latency can negatively impact the process of writing database files on disk. You can decrease latency and bottlenecks using SSD drives that are comparatively better than SATA or SCSI drives.
- Maintain Robust Server Infrastructure – The system needs to be properly built to ensure competent performance for various database operations. The greater the pressure on the resources, the greater the effect on performance.
- Follow ACID Properties – ACID properties make sure each transaction contains certain properties when it gets processed. In the case of data insertion, the isolation factor is also important to consider because the values have another source. Here, the statements should contain the suitable isolation level to maintain integrity within the database.
- Database Settings – One of the best ways to achieve improved outcomes is to maintain the right database configuration. This is because the settings can have a significant effect on performance. For instance, the location of the database files on the disk along with TempDB settings.
These are the various ways in which you can gain better performance at the query, trace, and constraint levels along with additions that can improve the execution of insert operations.
Heaps and clustered indexes are two different ways of storing data in SQL Server. Both have their advantages and disadvantages, and we will discuss them in this post.
A Bit about Heaps
Heaps are essentially piles of data that remain unsorted or unorganized, hence the name. Although you can find heaps on tables that don’t have clustered indexes, they may also be present with non-clustered indexes. Heaps provide the benefit of increased input speed which helps while adding data to a table. Data insertion is quicker because the process doesn’t require a logical order to do so.
A Bit about Clustered Indexes
A clustered index is a more organised way of data insertion. In fact, it is the go-to technique for logically sorting information in a table. A clustered index doesn’t need a primary key but you can create one on a predefined key-value. Most DBAs recommend creating them on the most-used columns that come under reference of highly frequent query executions. They also reduce the need for optimization since all the data gets sorted to fit them. The primary benefit of using a clustered index is that it speeds up data reads.
Knowing When to Use a Clustered Index
As noted above, using a clustered index leads to better read rates. Therefore, there are several instances where you may need to identify whether a clustered index will improve performance of SQL query rather than a heap.
To do this, you need to follow these steps:
- First, it is important to understand where there is a requirement for greater read speed.
- Check dynamic system views and look for large tables without a clustered index.
- Once you locate a few such tables, you can analyse the plans and stats of queries in the MSSQL system dynamic management views. Searching through the table name in the variable will show you the usage frequency of the plan. It will also show the text fetched and other necessary validation details that show whether a heap or non-clustered index is in use instead.
You will be able to view object names in the second result set in case the table in question is under use in SQL object. Once you have reviewed the query plans relevant to the use cases, you will have sufficient information to help you decide whether the table requires a clustered index or if a heap is more suitable for it. You will also have to choose all the columns that will have to be in the index in case of the former. Tables with several use cases that mostly share the same columns can provide result sets faster with a clustered index.
When Not to Use Clustered Indexes
This is just as important to know because believe it or not, there are instances where a clustered index can do more harm than good to oracle database performance.
A logging table is one such instance as it normally has far more insert operations than reads or updates. This is because their purpose is to log each occurrence but users may not refer to it as frequently. If you place an index on this kind of table, it can result in hot latches due to lagging data insertions for the last available page. Meanwhile, information keeps getting added onto the same page from other means. The one case where this issue doesn’t occur is when the index’s main column is a GUID, therefore, it isn’t sequential.
Using a clustered index in a table with an excessive number of columns isn’t the best idea, either. The reason behind this is simple: the index is supposed to define the default sort order. Too many columns mean repeated resorting with each new use case, slowing down the database. It will also result in an increase in the size of the non-clustered indexes present in the table.
Another situation where a clustered index can’t help is a column that isn’t usually static as they undergo frequent changes. Changing key values on an index have far greater chances of creating performance-related problems. This is because updating key values typically leads to page splits – these need maintenance, which takes resources and affects performance.