"The best thing about XML is what it shares with JSON, being human readable. That turns out to be important, not because people should be reading it, because we shouldn't, but because it avoids interoperability problems caused by fussy binary encoding issues.
Beyond that, there is not much to like. It is not very good as a data format. And it is not very good as a document format. If it were a good document format, then wikis would use it."
Beyond that, there is not much to like. It is not very good as a data format. And it is not very good as a document format. If it were a good document format, then wikis would use it."
Doug Crockford March 2010
This article describes a TSQL JSON parser and its evil twin, a JSON outputter, and provides the source. It is also designed to illustrate a number of string manipulation techniques in TSQL. With it you can do things like this to extract the data from a JSON document:
Select * from parseJSON('{
"Person":
{
"firstName": "John",
"lastName": "Smith",
"age": 25,
"Address":
{
"streetAddress":"21 2nd Street",
"city":"New York",
"state":"NY",
"postalCode":"10021"
},
"PhoneNumbers":
{
"home":"212 555-1234",
"fax":"646 555-4567"
}
}
}
')
And get:
...or you can do the round trip:
DECLARE @MyHierarchy JSONHierarchy
INSERT INTO @myHierarchy
select * from parseJSON('{"menu": {
"id": "file",
"value": "File",
"popup": {
"menuitem": [
{"value": "New", "onclick": "CreateNewDoc()"},
{"value": "Open", "onclick": "OpenDoc()"},
{"value": "Close", "onclick": "CloseDoc()"}
]
}
}}')
SELECT dbo.ToJSON(@MyHierarchy)
To get:
{
"menu" : {
"id" : "file",
"value" : "File",
"popup" : {
"menuitem" : [
{
"value" : "New",
"onclick" : "CreateNewDoc()"
},
{
"value" : "Open",
"onclick" : "OpenDoc()"
},
{
"value" : "Close",
"onclick" : "CloseDoc()"
}
]
}
}
}
Background
TSQL isn’t really designed for doing complex string parsing, particularly where strings represent nested data structures such as XML, JSON, YAML, or XHTML.
You can do it but it is not a pretty sight; but why would you ever want to do it anyway? Surely, if anything was meant for the 'application layer' in C# or VB.net, then this is it. 'Oh yes', will chime in the application thought police, 'this is far better done in the application or with a CLR.' Not necessarily.
Sometimes, you just need to do something inappropriate in TSQL.
There are a whole lot of reasons why this might happen to you. It could be that your DBA doesn’t allow a CLR, for example, or you lack the necessary skills with procedural code. Sometimes, there isn't any application, or you want to run code unobtrusively across databases or servers.
I needed to interpret or 'shred' JSON data. JSON is one of the most popular lightweight markup languages, and is probably the best choice for transfer of object data from a web page. It is, in fact, executable JavaScript that is very quick to code in the browser in order to dump the contents of a JavaScript object, and is lightning-fast to populate the browser object from the database since you are passing it executable code (you need to parse it first for security reasons - passing executable code around is potentially very risky). AJAX can use JSON rather than XML so you have an opportunity to have a much simpler route for data between database and browser, with less opportunity for error.
The conventional way of dealing with data like this is to let a separate business layer parse a JSON 'document' into some tree structure and then update the database by making a series of calls to it. This is fine, but can get more complicated if you need to ensure that the updates to the database are wrapped into one transaction so that if anything goes wrong, then the whole operation can be rolled back. This is why a CLR or TSQL approach has advantages.
"Sometimes, you just
need to do something
inappropriate in TSQL..."
need to do something
inappropriate in TSQL..."
I wrote the parser as a prototype because it was the quickest way to determine what was involved in the process, so I could then re-write something as a CLR in a .NET language. It takes a JSON string and produces a result in the form of an adjacency list representation of that hierarchy. In the end, the code did what I wanted with adequate performance (It reads a json file of 540 name\value pairs and creates the SQL hierarchy table in 4 seconds) so I didn't bother with the added complexity of maintaining a CLR routine. In order to test more thoroughly what I'd done, I wrote a JSON generator that used the same Adjacency list, so you can now import and export data via JSON!
These markup languages such as JSON and XML all represent object data as hierarchies. Although it looks very different to the entity-relational model, it isn't. It is rather more a different perspective on the same model. The first trick is to represent it as a Adjacency list hierarchy in a table, and then use the contents of this table to update the database. This Adjacency list is really the Database equivalent of any of the nested data structures that are used for the interchange of serialized information with the application, and can be used to create XML, OSX Property lists, Python nested structures or YAML as easily as JSON.
Adjacency list tables have the same structure whatever the data in them. This means that you can define a single Table-Valued Type and pass data structures around between stored procedures. However, they are best held at arms-length from the data, since they are not relational tables, but something more like the dreaded EAV (Entity-Attribute-Value) tables. Converting the data from its Hierarchical table form will be different for each application, but is easy with a CTE. You can, alternatively, convert the hierarchical table into XML and interrogate that with XQuery.
JSON format.
JSON is designed to be as lightweight as possible and so it has only two structures. The first, delimited by curly brackets, is a collection of name/value pairs, separated by commas. The name is followed by a colon. This structure is generally implemented in the application-level as an object, record, struct, dictionary, hash table, keyed list, or associative array. The other structure is an ordered list of values, separated by commas. This is usually manifested as an array, vector, list, or sequence.
"Using recursion in TSQL is
like Sumo Wrestlers doing Ballet.
It is possible but not pretty."
like Sumo Wrestlers doing Ballet.
It is possible but not pretty."
The first snag for TSQL is that the curly or square brackets are not 'escaped' within a string, so that there is no way of shredding a JSON 'document' simply. It is difficult to differentiate a bracket used as the delimiter of an array or structure, and one that is within a string. Also, interpreting a string into a SQL String isn't entirely straightforward since hex codes can be embedded anywhere to represent complex Unicode characters, and all the old C-style escaped characters are used. The second complication is that, unlike YAML, the datatypes of values can't be explicitly declared. You have to sniff them out from applying the rules from the JSON Specification.
Obviously, structures can be embedded in structures, so recursion is a natural way of making life easy. Using recursion in TSQL is like Sumo Wrestlers doing Ballet. It is possible but not pretty.
The implementation
Although the code for the JSON Parser/Shredder will run in SQL Server 2005, and even in SQL Server 2000 (with some modifications required), I couldn't resist using a TVP (Table Valued Parameter) to pass a hierarchical table to the function, ToJSON, that produces a JSON 'document'. Writing a SQL Server 2005 version should not be too hard.
First the function replaces all strings with tokens of the form @Stringxx, where xx is the foreign key of the table variable where the strings are held. This takes them, and their potentially difficult embedded brackets, out of the way. Names are always strings in JSON as well as string values.
Then, the routine iteratively finds the next structure that has no structure contained within it, (and is, by definition the leaf structure), and parses it, replacing it with an object token of the form '@Objectxxx', or '@arrayxxx', where xxxis the object id assigned to it. The values, or name/value pairs are retrieved from the string table and stored in the hierarchy table. Gradually, the JSON document is eaten until there is just a single root object left.
The JSON outputter is a great deal simpler, since one can be surer of the input, but essentially it does the reverse process, working from the root to the leaves. The only complication is working out the indent of the formatted output string.
In the implementation, you'll see a fairly heavy use of PATINDEX. This uses a poor man's RegEx, a starving man's RegEx. However, it is all we have, and can be pressed into service by chopping the string it is searching (if only it had an optional third parameter like CHARINDEX that specified the index of the start position of the search!). The STUFF function is also a godsend for this sort of string-manipulation work.
IF OBJECT_ID (N'dbo.parseJSON') IS NOT NULL
DROP FUNCTION dbo.parseJSON
GO
CREATE FUNCTION dbo.parseJSON( @JSON NVARCHAR(MAX))
RETURNS @hierarchy table
(
element_id int IDENTITY(1, 1) NOT NULL, /* internal surrogate primary key gives the order of parsing and the list order */
parent_id int, /* if the element has a parent then it is in this column. The document is the ultimate parent, so you can get the structure from recursing from the document */
object_id int, /* each list or object has an object id. This ties all elements to a parent. Lists are treated as objects here */
name nvarchar(2000), /* the name of the object */
stringvalue nvarchar(4000) NOT NULL, /*the string representation of the value of the element. */
valuetype nvarchar(100) NOT null /* the declared type of the value represented as a string in stringvalue*/
)
AS
BEGIN
DECLARE
@firstobject int, --the index of the first open bracket found in the JSON string
@opendelimiter int,--the index of the next open bracket found in the JSON string
@nextopendelimiter int,--the index of subsequent open bracket found in the JSON string
@nextclosedelimiter int,--the index of subsequent close bracket found in the JSON string
@type nvarchar(10),--whether it denotes an object or an array
@nextclosedelimiterChar CHAR(1),--either a '}' or a ']'
@contents nvarchar(MAX), --the unparsed contents of the bracketed expression
@start int, --index of the start of the token that you are parsing
@end int,--index of the end of the token that you are parsing
@param int,--the parameter at the end of the next Object/Array token
@endofname int,--the index of the start of the parameter at end of Object/Array token
@token nvarchar(4000),--either a string or object
@value nvarchar(MAX), -- the value as a string
@name nvarchar(200), --the name as a string
@parent_id int,--the next parent ID to allocate
@lenjson int,--the current length of the JSON String
@characters NCHAR(62),--used to convert hex to decimal
@result BIGINT,--the value of the hex symbol being parsed
@index SMALLINT,--used for parsing the hex value
@escape int --the index of the next escape character
/* in this temporary table we keep all strings, even the names of the elements, since they are 'escaped'
* in a different way, and may contain, unescaped, brackets denoting objects or lists. These are replaced in
* the JSON string by tokens representing the string
*/
DECLARE @strings table
(
string_id int IDENTITY(1, 1),
stringvalue nvarchar(MAX)
)
/* initialise the characters to convert hex to ascii */
SELECT
@characters = '0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ',
@parent_id = 0;
/* firstly we process all strings. This is done because [{} and ] aren't escaped in strings, which complicates an iterative parse. */
WHILE 1 = 1 /* forever until there is nothing more to do */
BEGIN
SELECT @start = PATINDEX('%[^a-zA-Z]["]%', @json collateSQL_Latin1_General_CP850_Bin); /* next delimited string */
IF @start = 0 BREAK /*no more so drop through the WHILE loop */
IF SUBSTRING(@json, @start+1, 1) = '"'
BEGIN /* Delimited name */
SET @start = @start+1;
SET @end = PATINDEX('%[^\]["]%', RIGHT(@json, LEN(@json+'|')-@start) collateSQL_Latin1_General_CP850_Bin);
END
IF @end = 0 /*no end delimiter to last string*/
BREAK /* no more */
SELECT @token = SUBSTRING(@json, @start+1, @end-1)
/* now put in the escaped control characters */
SELECT @token = REPLACE(@token, from_string, to_string)
FROM
(
SELECT '\"' AS from_string, '"' AS to_string
UNION ALL
SELECT '\\', '\'
UNION ALL
SELECT '\/', '/'
UNION ALL
SELECT '\b', CHAR(08)
UNION ALL
SELECT '\f', CHAR(12)
UNION ALL
SELECT '\n', CHAR(10)
UNION ALL
SELECT '\r', CHAR(13)
UNION ALL
SELECT '\t', CHAR(09)
) substitutions
SELECT @result = 0, @escape = 1
/*Begin to take out any hex escape codes*/
WHILE @escape > 0
BEGIN
/* find the next hex escape sequence */
SELECT
@index = 0,
@escape = PATINDEX('%\x[0-9a-f][0-9a-f][0-9a-f][0-9a-f]%', @token collateSQL_Latin1_General_CP850_Bin)
IF @escape > 0 /* if there is one */
BEGIN
WHILE @index < 4 /* there are always four digits to a \x sequence */
BEGIN
/* determine its value */
SELECT
@result =
@result + POWER(16, @index) * (CHARINDEX(SUBSTRING(@token, @escape + 2 + 3 -@index, 1), @characters) - 1), @index = @index+1 ;
END
/* and replace the hex sequence by its unicode value */
SELECT @token = STUFF(@token, @escape, 6, NCHAR(@result))
END
END
/* now store the string away */
INSERT INTO @strings
(stringvalue)
SELECT @token
/* and replace the string with a token */
SELECT @json = STUFF(@json, @start, @end + 1, '@string' + CONVERT(nvarchar(5),@@identity))
END
/* all strings are now removed. Now we find the first leaf. */
WHILE 1 = 1 /* forever until there is nothing more to do */
BEGIN
SELECT @parent_id = @parent_id + 1
/* find the first object or list by looking for the open bracket */
SELECT @firstobject = PATINDEX('%[{[[]%', @json collateSQL_Latin1_General_CP850_Bin) /*object or array*/
IF @firstobject = 0
BREAK
IF (SUBSTRING(@json, @firstobject, 1) = '{')
SELECT @nextclosedelimiterChar = '}', @type = 'object'
ELSE
SELECT @nextclosedelimiterChar = ']', @type = 'array'
SELECT @opendelimiter = @firstobject
WHILE 1 = 1 --find the innermost object or list...
BEGIN
SELECT @lenjson = LEN(@json+'|')-1
/* find the matching close-delimiter proceeding after the open-delimiter */
SELECT @nextclosedelimiter = CHARINDEX(@nextclosedelimiterChar, @json,@opendelimiter + 1)
/* is there an intervening open-delimiter of either type */
SELECT @nextopendelimiter = PATINDEX('%[{[[]%',RIGHT(@json, @lenjson-@opendelimiter) collate SQL_Latin1_General_CP850_Bin) /*object*/
IF @nextopendelimiter = 0
BREAK
SELECT @nextopendelimiter = @nextopendelimiter + @opendelimiter
IF @nextclosedelimiter < @nextopendelimiter
BREAK
IF SUBSTRING(@json, @nextopendelimiter, 1) = '{'
SELECT @nextclosedelimiterChar = '}', @type = 'object'
ELSE
SELECT @nextclosedelimiterChar = ']', @type = 'array'
SELECT @opendelimiter = @nextopendelimiter
END
/* and parse out the list or name/value pairs */
SELECT @contents = SUBSTRING(@json, @opendelimiter+1, @nextclosedelimiter-@opendelimiter - 1)
SELECT @json = STUFF(@json, @opendelimiter, @nextclosedelimiter - @opendelimiter +1, '@' + @type + CONVERT(nvarchar(5), @parent_id))
WHILE (PATINDEX('%[A-Za-z0-9@+.e]%', @contents collateSQL_Latin1_General_CP850_Bin)) < > 0
BEGIN /* WHILE PATINDEX */
IF @type = 'object' /*it will be a 0-n list containing a string followed by a string, number,boolean, or null*/
BEGIN
SELECT @end = CHARINDEX(':', ' '+@contents) /*if there is anything, it will be a string-based name.*/
SELECT @start = PATINDEX('%[^A-Za-z@][@]%', ' '+@contents collateSQL_Latin1_General_CP850_Bin) /*AAAAAAAA*/
SELECT
@token = SUBSTRING(' '+@contents, @start + 1, @end - @start - 1),
@endofname = PATINDEX('%[0-9]%', @token collate SQL_Latin1_General_CP850_Bin),
@param = RIGHT(@token, LEN(@token)-@endofname+1)
SELECT
@token = LEFT(@token, @endofname - 1),
@contents = RIGHT(' ' + @contents, LEN(' ' + @contents + '|') - @end - 1)
SELECT @name = stringvalue
FROM @strings
WHERE string_id = @param /*fetch the name*/
END
ELSE
BEGIN
SELECT @name = null
END
SELECT @end = CHARINDEX(',', @contents) /*a string-token, object-token, list-token, number,boolean, or null*/
IF @end = 0
SELECT @end = PATINDEX('%[A-Za-z0-9@+.e][^A-Za-z0-9@+.e]%', @contents+' 'collate SQL_Latin1_General_CP850_Bin) + 1
SELECT @start = PATINDEX('%[^A-Za-z0-9@+.e][A-Za-z0-9@+.e]%', ' ' + @contentscollate SQL_Latin1_General_CP850_Bin)
/*select @start,@end, LEN(@contents+'|'), @contents */
SELECT
@value = RTRIM(SUBSTRING(@contents, @start, @end-@start)),
@contents = RIGHT(@contents + ' ', LEN(@contents+'|') - @end)
IF SUBSTRING(@value, 1, 7) = '@object'
INSERT INTO @hierarchy (name, parent_id, stringvalue, object_id, valuetype)
SELECT @name, @parent_id, SUBSTRING(@value, 8, 5),
SUBSTRING(@value, 8, 5), 'object'
ELSE
IF SUBSTRING(@value, 1, 6) = '@array'
INSERT INTO @hierarchy (name, parent_id, stringvalue, object_id, valuetype)
SELECT @name, @parent_id, SUBSTRING(@value, 7, 5), SUBSTRING(@value, 7, 5),'array'
ELSE
IF SUBSTRING(@value, 1, 7) = '@string'
INSERT INTO @hierarchy (name, parent_id, stringvalue, valuetype)
SELECT @name, @parent_id, stringvalue, 'string'
FROM @strings
WHERE string_id = SUBSTRING(@value, 8, 5)
ELSE
IF @value IN ('true', 'false')
INSERT INTO @hierarchy (name, parent_id, stringvalue, valuetype)
SELECT @name, @parent_id, @value, 'boolean'
ELSE
IF @value = 'null'
INSERT INTO @hierarchy (name, parent_id, stringvalue, valuetype)
SELECT @name, @parent_id, @value, 'null'
ELSE
IF PATINDEX('%[^0-9]%', @value collate SQL_Latin1_General_CP850_Bin) > 0
INSERT INTO @hierarchy (name, parent_id, stringvalue, valuetype)
SELECT @name, @parent_id, @value, 'real'
ELSE
INSERT INTO @hierarchy (name, parent_id, stringvalue, valuetype)
SELECT @name, @parent_id, @value, 'int'
END /* WHILE PATINDEX */
END /* WHILE 1=1 forever until there is nothing more to do */
INSERT INTO @hierarchy (name, parent_id, stringvalue, object_id, valuetype)
SELECT '-', NULL, '', @parent_id - 1, @type
RETURN
END
GO
So once we have a hierarchy, we can pass it to a stored procedure. As the output is an adjacency list, it should be easy to access the data. You might find it handy to create a table type if you are using SQL Server 2008. Here is what I use. (Note that if you drop a Table Valued Parameter type, you will have to drop any dependent functions or procedures first, and re-create them afterwards).
-- Create the data type
IF EXISTS (SELECT * FROM sys.types WHERE name LIKE 'JSONHierarchy')
DROP TYPE dbo.JSONHierarchy
go
CREATE TYPE dbo.JSONHierarchy AS TABLE
(
element_id INT NOT NULL, /* internal surrogate primary key gives the order of parsing and the list order */
parent_ID INT,/* if the element has a parent then it is in this column. The document is the ultimate parent, so you can get the structure from recursing from the document */
Object_ID INT,/* each list or object has an object id. This ties all elements to a parent. Lists are treated as objects here */
NAME NVARCHAR(2000),/* the name of the object, null if it hasn't got one */
StringValue NVARCHAR(MAX) NOT NULL,/*the string representation of the value of the element. */
ValueType VARCHAR(10) NOT null /* the declared type of the value represented as a string in StringValue*/
PRIMARY KEY (element_id)
)
ToJSON. A function that creates JSON Documents
Firstly, we need a simple utility function:
IF OBJECT_ID (N'dbo.parseJSON') IS NOT NULL
DROP FUNCTION dbo.JSONEscaped
GO
CREATE FUNCTION JSONEscaped ( /* this is a simple utility function that takes a SQL String with all its clobber and outputs it as a sting with all the JSON escape sequences in it.*/
@Unescaped NVARCHAR(MAX) --a string with maybe characters that will break json
)
RETURNS NVARCHAR(MAX)
AS
BEGIN
SELECT @Unescaped = REPLACE(@Unescaped, FROMString, TOString)
FROM (SELECT
'\"' AS FromString, '"' AS ToString
UNION ALL SELECT '\', '\\'
UNION ALL SELECT '/', '\/'
UNION ALL SELECT CHAR(08),'\b'
UNION ALL SELECT CHAR(12),'\f'
UNION ALL SELECT CHAR(10),'\n'
UNION ALL SELECT CHAR(13),'\r'
UNION ALL SELECT CHAR(09),'\t'
) substitutions
RETURN @Unescaped
END
And now, the function that takes a JSON Hierarchy table and converts it to a JSON string.
IF OBJECT_ID (N'dbo.ToJSON') IS NOT NULL
DROP FUNCTION dbo.ToJSON
GO
CREATE FUNCTION ToJSON
(
@Hierarchy JSONHierarchy READONLY
)
RETURNS NVARCHAR(MAX)--JSON documents are always unicode.
AS
BEGIN
DECLARE
@JSON NVARCHAR(MAX),
@NewJSON NVARCHAR(MAX),
@Where INT,
@ANumber INT,
@notNumber INT,
@indent INT,
@CrLf CHAR(2)--just a simple utility to save typing!
--firstly get the root token into place
SELECT @CrLf=CHAR(13)+CHAR(10),--just CHAR(10) in UNIX
@JSON = CASE ValueType WHEN 'array' THEN '[' ELSE '{' END
+@CrLf+ '@Object'+CONVERT(VARCHAR(5),OBJECT_ID)
+@CrLf+CASE ValueType WHEN 'array' THEN ']' ELSE '}' END
FROM @Hierarchy
WHERE parent_id IS NULL AND valueType IN ('object','array') --get the root element
/* now we simply iterate from the root token growing each branch and leaf in each iteration. This won't be enormously quick, but it is simple to do. All values, or name/value pairs withing a structure can be created in one SQL Statement*/
WHILE 1=1
begin
SELECT @where= PATINDEX('%[^[a-zA-Z0-9]@Object%',@json)--find NEXT token
if @where=0 BREAK
/* this is slightly painful. we get the indent of the object we've found by looking backwards up the string */
SET@indent=CHARINDEX(char(10)+char(13),Reverse(LEFT(@json,@where))+char(10)+char(13))-1
SET @NotNumber= PATINDEX('%[^0-9]%', RIGHT(@json,LEN(@JSON+'|')-@Where-8)+' ')--find NEXT token
SET @NewJSON=NULL --this contains the structure in its JSON form
SELECT @NewJSON=COALESCE(@NewJSON+','+@CrLf+SPACE(@indent),'')
+COALESCE('"'+NAME+'" : ','')
+CASE valuetype
WHEN 'array' THEN ' ['+@CrLf+SPACE(@indent+2)
+'@Object'+CONVERT(VARCHAR(5),OBJECT_ID)+@CrLf+SPACE(@indent+2)+']'
WHEN 'object' then ' {'+@CrLf+SPACE(@indent+2)
+'@Object'+CONVERT(VARCHAR(5),OBJECT_ID)+@CrLf+SPACE(@indent+2)+'}'
WHEN 'string' THEN '"'+dbo.JSONEscaped(StringValue)+'"'
ELSE StringValue
END
FROM @Hierarchy WHERE parent_id= SUBSTRING(@JSON,@where+8, @Notnumber-1)
/* basically, we just lookup the structure based on the ID that is appended to the @Object token. Simple eh? */
--now we replace the token with the structure, maybe with more tokens in it.
Select @JSON=STUFF (@JSON, @where+1, 8+@NotNumber-1, @NewJSON)
end
return @JSON
end
ToXML. A function that creates XML
The function that converts a hierarchy table to XML gives us a JSON to XML converter. It is surprisingly similar to the previous function
IF OBJECT_ID (N'dbo.ToXML') IS NOT NULL
DROP FUNCTION dbo.ToXML
GO
CREATE FUNCTION ToXML
(
/*this function converts a JSONhierarchy table into an XML document. This uses the same technique as the toJSON function, and uses the 'entities' form of XML syntax to give a compact rendering of the structure */
@Hierarchy JSONHierarchy READONLY
)
RETURNS NVARCHAR(MAX)--use unicode.
AS
BEGIN
DECLARE
@XMLAsString NVARCHAR(MAX),
@NewXML NVARCHAR(MAX),
@Entities NVARCHAR(MAX),
@Objects NVARCHAR(MAX),
@Name NVARCHAR(200),
@Where INT,
@ANumber INT,
@notNumber INT,
@indent INT,
@CrLf CHAR(2)--just a simple utility to save typing!
--firstly get the root token into place
--firstly get the root token into place
SELECT @CrLf=CHAR(13)+CHAR(10),--just CHAR(10) in UNIX
@XMLasString ='<?xml version="1.0" ?>
@Object'+CONVERT(VARCHAR(5),OBJECT_ID)+'
'
FROM @hierarchy
WHERE parent_id IS NULL AND valueType IN ('object','array') --get the root element
/* now we simply iterate from the root token growing each branch and leaf in each iteration. This won't be enormously quick, but it is simple to do. All values, or name/value pairs within a structure can be created in one SQL Statement*/
WHILE 1=1
begin
SELECT @where= PATINDEX('%[^a-zA-Z0-9]@Object%',@XMLAsString)--find NEXT token
if @where=0 BREAK
/* this is slightly painful. we get the indent of the object we've found by looking backwards up the string */
SET@indent=CHARINDEX(char(10)+char(13),Reverse(LEFT(@XMLasString,@where))+char(10)+char(13))-1
SET @NotNumber= PATINDEX('%[^0-9]%', RIGHT(@XMLasString,LEN(@XMLAsString+'|')-@Where-8)+' ')--find NEXT token
SET @Entities=NULL --this contains the structure in its XML form
SELECT @Entities=COALESCE(@Entities+' ',' ')+NAME+'="'
+REPLACE(REPLACE(REPLACE(StringValue, '<', '<'), '&', '&'),'>', '>')
+ '"'
FROM @hierarchy
WHERE parent_id= SUBSTRING(@XMLasString,@where+8, @Notnumber-1)
AND ValueType NOT IN ('array', 'object')
SELECT @Entities=COALESCE(@entities,''),@Objects='',@name=CASE WHEN Name='-' THEN'root' ELSE NAME end
FROM @hierarchy
WHERE [Object_id]= SUBSTRING(@XMLasString,@where+8, @Notnumber-1)
SELECT @Objects=@Objects+@CrLf+SPACE(@indent+2)
+'@Object'+CONVERT(VARCHAR(5),OBJECT_ID)
--+@CrLf+SPACE(@indent+2)+''
FROM @hierarchy
WHERE parent_id= SUBSTRING(@XMLasString,@where+8, @Notnumber-1)
AND ValueType IN ('array', 'object')
IF @Objects='' --if it is a lef, we can do a more compact rendering
SELECT @NewXML='<'+COALESCE(@name,'item')+@entities+' />'
ELSE
SELECT @NewXML='<'+COALESCE(@name,'item')+@entities+'>'
+@Objects+@CrLf++SPACE(@indent)+'</'+COALESCE(@name,'item')+'>'
/* basically, we just lookup the structure based on the ID that is appended to the @Object token. Simple eh? */
--now we replace the token with the structure, maybe with more tokens in it.
Select @XMLasString=STUFF (@XMLasString, @where+1, 8+@NotNumber-1, @NewXML)
end
return @XMLasString
end
This provides you the means of converting a JSON string into XML
DECLARE @MyHierarchy JSONHierarchy,@xml XML
INSERT INTO @myHierarchy
select * from parseJSON('{"menu": {
"id": "file",
"value": "File",
"popup": {
"menuitem": [
{"value": "New", "onclick": "CreateNewDoc()"},
{"value": "Open", "onclick": "OpenDoc()"},
{"value": "Close", "onclick": "CloseDoc()"}
]
}
}}')
SELECT dbo.ToXML(@MyHierarchy)
SELECT @XML=dbo.ToXML(@MyHierarchy)
SELECT @XML
This gives the result...
<?xml version="1.0" ?>
<root>
<menu id="file" value="File">
<popup>
<menuitem>
<item value="New" onclick="CreateNewDoc()" />
<item value="Open" onclick="OpenDoc()" />
<item value="Close" onclick="CloseDoc()" />
</menuitem>
</popup>
</menu>
</root>
(1 row(s) affected)
<root><menu id="file" value="File"><popup><menuitem><item value="New" onclick="CreateNewDoc()" /><item value="Open" onclick="OpenDoc()" /><item value="Close" onclick="CloseDoc()" /></menuitem></popup></menu></root>
(1 row(s) affected)
Wrap-up
The so-called 'impedence-mismatch' between applications and databases is, I reckon, an illusion. The object-oriented nested data-structures that we receive from applications are, if the developer has understood the data correctly, merely a perspective from a particular entity of the relationships it is involved with. Whereas it is easy to shred XML documents to get the data from it to update the database, it has been trickier with other formats such as JSON. By using techniques like this, it should be possible to liberate the application, or website, programmer from having to do the mapping from the object model to the relational, and spraying the database with ad-hoc TSQL that uses the base tables or updateable views. If the database can be provided with the JSON, or the Table-Valued parameter, then there is a better chance of maintaining full transactional integrity for the more complex updates.
The database developer already has the tools to do the work with XML, but why not the simpler, and more practical JSON? I hope these two routines get you started with experimenting with this.
