Json in sql server pdf download

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Submit and view feedback for This product This page. Inserting a Child Element with Position Specification Problem You want to insert a new element into the existing element group and enforce a certain position sequence.

The syntax for as first and as last differs slightly from the syntax for after and before. Solution Unlike attributes, where you can add several attributes and their values by separating them with a comma, multiple elements are not supported in a direct insert within the modify method. However, the XQuery extension function sql:variable helps solve the problem, as shown in Listing How It Works As explained in the Solution section, the modify method does not support a multiple sibling element list within the insert directive.

The XQuery sql:variable extension function provides us a reference to an XML block, which makes the insert directive mechanism operate as it inserts a new element.

Assign an XML element list to the variable. Solution The modify method replace value of statement updates an XML instance element value. The insert process has many options for XML instances. Compared to insert, updating an XML instance element is fairly straightforward.

To modify the XML instance element value, you need the following: 1. Specify the modify method replace value of statement.

Opening parenthesis, provide the XPath path to the XML element; implement the text function for the target element; and closing the parenthesis and specifying the singleton. After the with keyword, specify a new element value in double quotes. Solution Updating an XML instance attribute solution is relatively close to updating the element. However, updating the attribute has some specifics that are demonstrated in Listing To modify the XML instance attribute value, you need to: 1.

The XPath path to the XML attribute you want to update with the symbol preceding the attribute name, wrapped in parentheses. The XPath path must be a singleton node. After the with keyword, specify a new attribute value in double quotes.

The major difference between modifying the element and attribute is that the attribute must be prefixed with an symbol and the text node test is not needed to update the attribute. Solution Use the delete statement in the modify method, as shown in Listing To delete an attribute from an XML instance, the modify method needs the delete statement and an XPath path to the attribute. Also, the ProductDescription element is unique within the XML document, therefore no singleton needed in such a case.

Solution The mechanism for removing an element from an XML instance is very similar to removing an attribute. In the next chapter the recipes will cover how to efficiently filter the XML. This chapter will demonstrate many examples of how to implement filters for XQuery requests.

Solution The exist method allows you to determine whether an element or attribute exists within an XML instance. Listing is a demonstration of using the exist method to retrieve all XML instances containing the YearlyIncome element directly below the root IndividualSurvey element.

The root element is IndividualSurvey, and it can contain up to 13 child elements. The same mechanism is used to detect an attribute, with some minor syntax differences required by XQuery to match attributes.

The XML provided from the Demographics column does not have attributes. Sample demonstrates when the YearlyIncome element has the attribute currency. Sample Solution The exist method can provide filtering against XML text nodes, especially when the XML instances need to be inspected for a specific searching condition.

When the query returns columns from a table and the XML instance is not a required part of the shredding processes, but at the same time the rows from the table need to be filtered based on XML value, then the exist Method can be used as the filtering mechanism to return rows based on the search condition.

The difference, as demonstrated in Recipe , is that the exist Method has a filter condition for the TotalPurchaseYTD element value instead of checking for the existence of an element, for example: Demographics.

The filter argument for the exist Method has the following components: 1. It is the basis for node order comparisons. For example, TotalPurchaseYTD element expects an xs:decimal type, but the value is implemented as an xs:string type. The exceptions are the date, time, and datetime types, where XML filters directly handle conversion, as shown in Listing When it appears at the beginning of an XQuery path expression, it retrieves all nodes in the XML data.

You can use this in the node method to avoid explicitly specifying a full reference to the target element, as shown in Listing The XQuery engine uses this when searching for all occurrences of an element contained within the XML data that the nodes method is acting upon. The hierarchy for the Tel. Number element that is part of the HumanResources. Number element hierarchy The fully qualified XQuery path expression for the nodes method to the Tel. Number element is demonstrated in Listing However, this technique should be tested thoroughly before coming to a final consideration because it could cause performance problems during the XML shredding process.

Chapter 7 will provide more details about the nodes method performance optimization. Solution Set the filter within the nodes Method, Listing To set a single value filter within the nodes method you need: 1. Because those two methods serve completely different functions, the exist method is for filtering, and nodes is for shredding.

The best implementation and demonstration of the sql:variable function is a stored procedure, as shown in Listing The sql:variable function could be a part of the nodes and exist Methods to provide filtering functionalities.

However, the solution is much simpler. However, when your task requires you to filter values using fn:starts- with or fn:ends-with -type functionality, you can complete this task by using an XQuery and T-SQL hybrid solution, as shown in Listing Solution The XQuery logical and operator can be used to join two predicates to define a range filter for an XML instance, as shown in Listing Solution XQuery provides the and and or logical operators to create compound predicates, which implement multiple filtering conditions against an XML instance, as shown in Listing The logic in this recipe is to filter the XML instance where: 1.

This recipe demonstrates the two logical operators and and or. Person and the column Demographics, containing 19, rows, has been selected for this chapter. However, the Demographics column is element-centric XML. Therefore, no filtering samples were provided for the XML attribute. There is a small difference when referencing the XML attribute. Solution The XQuery negation function is fn:not. When wrapped around an XQuery predicate, fn:not returns the opposite of the Effective Boolean Value of the predicate.

Logically, fn:empty provides functionality to detect any empty values within your XML data. The Solution section demonstrates the syntax to return rows where the Occupation element has a value, that is, the element is not empty. Therefore, both fn:not and fn:empty are implemented in Listing IndividualSurvey[ fn:not fn:empty Occupation As mentioned in the Solution section, the fn:empty function is an alternate to the exist Method, Listing However, as was demonstrated in the previous recipes, XQuery has sufficient ability to filter an XML instance.

Therefore, XQuery filtering should be your first choice. Indexes are a front runner to improve data delivery processes. However, the logical tree structure of XML data cannot be indexed in the same way as plain old relational data. To demonstrate, we will create a new table with an XML column, populate it with data, and then create a primary XML index on it.

Listing demonstrates how to create a primary XML index on the Demographic column of our new table. Listing shows the SQL code that creates the table and loads it with data from the Person. Person table in the AdventureWorks database. Note the session- level settings shown via the SET statements.

These steps specify the XML runtime shredding mechanism and is very similar to a table scan for a normal relational SQL query. That means, depending on how big your XML instance is, the XML shredding process could potentially be very costly in terms of performance. All XML indexes must be dropped before modifying the primary key. The XML indexes must be dropped before the column type can be changed. However, there are several considerations associated with XML indexing.

First of all, adding a primary XML index might consume a large amount of storage space. That could potentially consume more than double the storage space required to store the unindexed XML data. An XML index is worth considering if you are querying against a large number of rows at a time or if your XML data is large in size. If these conditions do not apply, then the storage cost could outweigh the efficiency.

Listing creates the same table from Solution and applies a primary XML index to it, as these are both required for this solution. Listing demonstrates how to create a secondary path XML index on the table. Listing specifies a query for the existence of an XQuery path. Solution A secondary value type XML index benefits XQuery performance when the path is not fully specified or if it includes a wildcard. Listing creates the sample table and primary XML index we previously created in Solutions and If you have already created this table, then you do not need to recreate it.

Listing demonstrates XQuery benefits from using a value index. However, this technique could slow down performance for an XML data type column where the XML instance has deeply nested elements. This is one of the most common performance issues in the XML shredding process. Therefore, I would recommend when possible to provide a more detailed path within the nodes method.

Listing creates our demonstration table we have used in Solutions , and , and creates the primary XML index on it. The selective XML index acts against the values are specified in one or more paths. The index contains the nodes that are identified by the paths.

For example, if you want to improve search on the Resume column of the HumanResources. JobCandidate table. Listing shows how to query an XML column with a namespace. Solution Implementing the hints can optimize a selective XML index. Listing demonstrates different hints for the selective XML index. Check for node existence. Avoid adding additional instances subsequently, as this can cause issues. An issue could arise if something breaks the data type, then a null will show in the index.

JobCandidate table from Solution , which is a prerequisite for this solution. Solution You can add or remove a path on a selective XML index. Listing creates the demonstration table we previously created in Solution This is a prerequisite for this solution.

Wrapping up This chapter completes the XML section of the book. I hope that you learned a lot from the recipes provided in the XML portion. Microsoft recommends storing JSON as an nvarchar max.

Listing TopObject is an object block. An empty array [] is also considered valid JSON data. The key of a member should be contained in double quotes. A key must be unique within the structure of an object. String type and date type values of a member are required to be contained in double quotes. Boolean and numeric values should not be contained within double quotes.

However, when Boolean values use true or false literals, those values should be in lowercase. Numbers with leading zeroes are considered strings. Therefore, they are required to be contained within double quotes. Each member of an object and each array value must be followed by a comma, except the last key-value pair.

These types hierarchyid return an error. Data type hierarchyid does not require explicit conversion. Listing demonstrates a formatted JSON from the query result.

Customers table. The result, by default, is displayed in the SSMS grid as a hyperlink. However, the result will load as an unformatted single-line string. However, for a bigger JSON, manual formatting could take an enormous time to complete such a task. This program is easy to operate: 1. Click Process button. For example, Listing demonstrates the JSON built with a query where the query does not have table and column aliases.

Listing displays the query result in JSON output. Listing is showing JSON output generated by the query. Therefore, key elements will be missing in the JSON output. Listing demonstrates the query and returned JSON output. Listing demonstrates JSON output without square brackets []. That creates a JSON output as an initial array instead of an object. However, some output does not require the surrounding brackets. Remove one of these options. When alias names are separated by a comma, a parent-child level is established for the elements and value.

Database 2. However, there is one problem with the resulting output. Ideally, it would be more efficient to return the Columns section as an array instead of an object and list all columns inside the array. This way, the JSON structure will look slightly different. Listing demonstrates JSON structure with the Columns section as an array, where the ColumnName key element and values are surrounded by square brackets [].

Columns' FROM sys. I intentionally demonstrated two ways to create a JSON output. In some cases, you need object-oriented JSON as it is demonstrated in Listings and , and in another case you need to create compact JSON with an array of values as demonstrated in Listings and Listing demonstrates the JSON output. To create table CustomerInvoice, run Listing first. JSON Expression, required. JSON Path, optional. Listing demonstrates a query where the Customers.

Listing shows the JSON output. Therefore, any other spelling than a properly cased ToString function will raise an error. For example, SQL Server raises an error when the function is spelled tostring. Listing demonstrates the error message. SqlGeography' in assembly 'Microsoft. Listing demonstrates a query where the column Customers.

DeliveryLocation with the geography data type is explicitly converted to nvarchar using the CAST function. This chapter covered how to build efficient and effective JSON output. The next chapter will cover the conversion of JSON values into rows and columns.

You will find a variety of tested samples and possible scenarios to help you find the most appropriate solution for your task. Content is presented in the popular problem-solution format. Look up the problem that you want to solve. Read the solution.

Apply the solution directly in your own code. Problem solved! Its scripting capabilities are robust and flexible, allowing you to simplify automation and integration across different Microsoft applications and components. You will learn about basic SQL Server administration tasks and then get to know about some security-related topics such as the authentication mode and assigning permissions.

Moving on, you will explore different methods to back up and restore your databases and perform advanced administration tasks such as working with Policies, Filetables, and SQL audits. Towards the end of the book, you will find some useful information, which includes a PowerShell tutorial for novice users, some commonly-used PowerShell and SQL Server syntax, and a few online resources.

All these concepts will help you to efficiently manage your administration tasks. Each recipe is followed by an analysis of the steps or design decisions taken and additional information about the task at hand.

Working scripts are provided for all examples so that you can dive in right away. You can read this book sequentially by chapter or you can pick and choose which topics you need right away.

Make use of hands-on recipes for many tasks that are typically encountered in both the on-premises as well as the cloud world. Key Features A recipe-based guide to help you build effective administrative solutions Gain hands-on experience with the newly added features of PowerShell Core Manage critical business environments with professional scripting practices Book Description This book will follow a recipe-based approach and start off with an introduction to the fundamentals of PowerShell, and explaining how to install and run it through simple examples.

Next, you will learn how to use PowerShell to access and manipulate data and how to work with different streams as well. You will also explore the object model which will help with regard to PowerShell function deployment.

Going forward, you will get familiar with the pipeline in its different use cases. The next set of chapters will deal with the different ways of accessing data in PowerShell. The last set of chapters will help you understand the management of a private and public cloud with PowerShell Core.

You will also learn how to access web services and explore the high-performance scripting methods. By the end of this book, you will gain the skills to manage complex tasks effectively along with increasing the performance of your environment.

What you will learn Leverage cross-platform interaction with systems Make use of the PowerShell recipes for frequent tasks Get a better understanding of the inner workings of PowerShell Understand the compatibility of built-in Windows modules with PowerShell Core Learn best practices associated with PowerShell scripting Avoid common pitfalls and mistakes Who this book is for This book will be for windows administrators who want to enhance their PowerShell scripting skills to the next level.

System administrators wanting to automate common to complex tasks with PowerShell scripts would benefit from this book. Prior understanding on PowerShell would be necessary. You may know SQL basics, but are you taking advantage of its expressive power? This second edition applies a highly practical approach to Structured Query Language SQL so you can create and manipulate large stores of data. SQL programmers, analysts, data scientists, database administrators, and even relatively casual SQL users will find SQL Cookbook to be a valuable problem-solving guide for everyday issues.

No other resource offers recipes in this unique format to help you tackle nagging day-to-day conundrums with SQL. The book shows you how to view data from multiple perspectives, including data frame and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations.

You will learn to manipulate data and get them down to a form that can be useful for making the right decisions. Microsoft Silverlight is a cross-browser, cross-platform plug-in like Flash that delivers rich interactive applications for the Web. Silverlight offers a flexible programming model that supports a number of different programming languages and techniques making it cross-platform and all major browsers cross-browser support. Silverlight 1. Readers will enjoy the "cut-and-paste" ready solutions that give lots of bang for their buck.