Precisely Simply Ways To Acquire Sql Internet Web Server Business Intelligence Development Workshop 2008 – The diagram contains two boxes, one for Azure components and one for on-premises components. Outside the Azure box is a data file labeled J S O N. An arrow points from the J S O N file to an API Management icon inside the Azure box. A second arrow points from the API Management icon to a Logic Apps icon that is also inside the Azure box. Three arrows point away from the Logic Apps icon. One leads to a Key Vault icon which is inside the Azure box. One leads to a local data gateway icon found between the two boxes. And the third one leads to an Azure Monitor icon which is inside the Azure box. Another arrow points from the gateway to a SQL Server icon inside the local box. A final arrow points from the SQL Server icon to a person outside of the local box.
A logic app can store HTTP request data in a SQL Server database. Because Logic Apps works as a secure Azure API Management endpoint, calls to its API can trigger various data-related tasks. In addition to updating local databases, you can also send teams or email messages.
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With the serverless model used by Logic Apps, the service automatically scales to meet demand. But be aware of the limits on read and write operations with the on-premises data gateway.
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The profiles do not include the costs of a SQL Server database. To tune the parameters and explore the cost of running this solution in your environment, use the Azure pricing calculator. Almost every application or piece of software interacts with a database of some kind, particularly relational databases. Although there are several languages for manipulating relational databases, SQL remains a standard. Although SQL is a robust language, it does have some limitations.
To overcome the limitations of SQL, many companies have introduced programming languages to create applications that interact with SQL databases, for example, Oracle’s PL/SQL.
PL/SQL (Procedural Language Extensions to Structured Query Language) is an easy-to-use programming language that makes it easy to create powerful SQL queries. Although the term itself is specific to the Oracle programming language, the general concept of extending SQL queries with procedural logic applies to many programming languages (for example, Microsoft’s T-SQL). However, to keep this article simple, we will refer to PL/SQL throughout.
PL/SQL applications combine procedural logic and SQL statements to retrieve and process data from an SQL database. Because they switch between procedural code and SQL queries, PL/SQL applications can be inefficient. But you can optimize this interface by using collections of data types, which makes PL/SQL applications faster and more efficient.
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Although there are many benefits to using other programs like Java, they each have their own specialties. PL/SQL is purely server-side and focuses on interacting with the relational database. Java is an object-oriented language that has both client-side and server-side functionality. If your focus is on non-database-oriented functionality, Java is your choice. But when it comes to pure database functionality, Java code can slow down the speed and performance of the application. Because PL/SQL is tightly integrated with SQL and the underlying database, properly created PL/SQL code can limit the number of database calls required, speeding up data access.
What are some of the possible problems with using Java for database-intensive applications? For one, imposing an object-oriented structure on the database can lead to unnecessary database connections, consuming resources and slowing down. Java can also preload large data sets, which reduces overall application performance.
Can you use PL/SQL and Java together? Absolutely. PL/SQL can call Java and vice versa. Those programmers who are comfortable with PL/SQL and Java can and should find ways to optimize overall application performance by distributing tasks where they are best suited and performed most efficiently. If you are familiar with simple relational database programming, PL/SQL is a good choice for you. If you’re strong in object-oriented programming, you shouldn’t have a problem using both.
Each language has its supporters and detractors, and you should carefully consider both the needs of your particular application and your own programming skills when selecting whether to use PL/SQL, Java, both, or another language.
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Collections are essentially groups of indexed data that have the same type, for example arrays or lists (arrays for example are collections of elements based on indexes). Most programming languages in general provide support for collections.
Collections reduce the number of database calls due to caching (cached by the collections themselves) of regularly accessed static data. Call reduction equals increased speed and efficiency. Collections can also reduce the total code required for an application, further increasing efficiency.
Each element in a collection has a unique identifier called a subscript. Collections come with their own set of methods to operate on individual elements. PL/SQL includes methods to manipulate individual elements or the collection in bulk.
PL/SQL uses three types of collections: associative arrays, nested tables, and varrays. Choosing the right collection (or collections) for your application requires understanding the differences between collection types and how each one works. The main differences are:
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Earlier versions of PL/SQL used what were first known as PL/SQL tables and then indexed tables. In a PL/SQL table, the collections were indexed using an integer. The individual elements of the collection could then be referenced using the value of the index.
Because it wasn’t always easy to identify an element by its subscript, PL/SQL tables evolved to include alphanumeric string indexing. The ability to index by the data itself instead of the index value makes it easier and faster to identify data for manipulation, such as deletion or updating.
PL/SQL tables or indexed tables are now known as associative arrays. Associative arrays are one-dimensional collections, also known as sets of key-value pairs. You can think of it as a single column table. Multidimensional associative arrays can be created by making collections of collections.
Associative arrays have no limits, so you don’t need to specify a size when creating one. They can be dense or scattered. You can, for example, set the values of elements 1, 3, 10, and 200 of an associative array without setting values for any other elements. However, associative arrays must be stored in the PL/SQL application rather than in the SQL database, so they cannot be manipulated with SQL statements.
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Associative arrays are your best option when you prioritize indexing speed and flexibility over storage location. A real life use case for associative arrays would be in fundamental programming programming patterns (such as rote, or where function calls return to the original cached result to help speed up programs).
Like associative arrays, nested tables are unlimited and do not require size specification on creation. Nested tables always start out as dense collections of elements with sequential subscripts. However, because nested tables allow manipulation of individual elements, nested tables can become sparse due to element deletion.
Nested tables can be created in the database or in a PL/SQL block at the application level. When nested tables are created in the database, they are stored in a separate database table from other columns. However, all nested table types for a database table are stored together in the same separate database table.
Nested tables are your best option when you need the ability to dynamically modify individual elements, either the number of elements or the content of the elements. Nested tables are also useful when you want to store items in the SQL database instead of the PL/SQL application.
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Varrays (short for variable arrays) are bounded: creating a varray requires setting the maximum number of elements for the varray. Therefore, Varrays are useful for storing sequential, fixed-size collections of elements that have the same type.
Varrays store elements in the same order they are added to the array at contiguous memory addresses. The lowest address represents the first element of the varray and the highest address represents the last element.
Although the initial size of a varray is fixed, each of the individual elements has maximum sizes that can be changed dynamically. Also, you can modify the length of a varray using the
Methods. However, individual elements within a varray (other than the endpoints) cannot be updated or deleted, and therefore varrays are always dense.
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Varrays are your best choice when you’re working with a fixed, delimited set of elements, for example, when you need to preserve an ordered list. Varrays are also useful when you need or want to store data in the SQL database itself.
As a basis for providing example coding for the different collection types, we will use the following example.
Suppose you work as a cybersecurity professional in the IT department of a large corporation. The IT manager asks you to start creating monthly logs of identified vulnerabilities created by SQL injections, identifying the top four vulnerability types each month by location.
In addition, for each vulnerability, you must record severity-specific information from various sources, including the National Vulnerability Database (NVD) Common Vulnerability and Exposure (CVE) identification number, Weakness Enumeration identification number (CWE), the Common Vulnerability Scoring System (CVSS) Score identification number, and the SQL injection vulnerability type.
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