SQL Query Engine

ICONICS Hyper Historian logs data to a proprietary database. While you can use the TrendWorX64 and TrendWorX32 Viewers to see and edit your logged data in a graphical format, you may wish to create reports for the logged data or edit data in bulk. For this reason, Hyper Historian comes with a SQL Provider that allows you to use common SQL Data Manipulation Language (DML) queries to retrieve and edit data.

This topic provides the following information:

General Requirements

Provider Capabilities and Limitations

Architecture

Data Architecture

Supported SQL Constructs

Historical Aggregates

Specifying a Connection

Microsoft SQL Server Specifics

Troubleshooting

Examples

To get started, refer to the SQL Query Engine Quick Start topic.

General Requirements

VC Redistributable files for VS2012, ICONICS Hyper Historian, Microsoft SQL Server 2005 (or higher) and Microsoft SQL Management Studio, Microsoft Excel 2003 (or higher) installed on machine.

Provider Capabilities and Limitations

Testing and Validating

The HyperHistorian SQL Query Engine is developed, tested and validated against the Microsoft OLE DB RowsetViewer (version 2.70.7531.0).

SQL Capabilities

Due to the provider's nature, a limited range of SQL features is supported. Catalogs, schemata and tables are predefined (by the Hyper Historian HDA Server). You can use only DML (Data Manipulation Language) queries (i.e. SELECT, INSERT, UPDATE and DELETE). Also, the stored procedures are implemented in the Hyper Historian SQL Query Engine.

Individual query types have specific limitations to the query structure, as well. These limitations are detailed in an appropriate query section. In addition, advanced consumers (e.g. Microsoft SQL Server) may perform query analysis (or preprocessing) and may change the original query. This may lead to unexpected results. These rarities will be described later.

Architecture

ICONICS' Hyper Historian SQL Query Engine was developed as an in-proc COM server. The whole provider is divided into several DLL libraries (modules). You can use the provider in 32-bit and 64-bit clients.

32-bit binaries (needed every time)

• GenericOleDbProvider.dll

• HHOleDbProvider.dll

• HHRawDataProvider.exe

• RawDataProviderPS.dll

64-bit binaries (needed for the 64-bit clients)

• GenericOleDbProvider64.dll

• HHOleDbProvider64.dll

• RawDataProviderPS64.dll

GenericOleDbProvider.dll, GenericOleDbProvider64.dll -- This module communicates with a SQL client. The module processes data from the HHRawDataProvider.exe and provides it in the form of tables and stored procedures to the client.

HHOleDbProvider.dll, HHOleDbProvider64.dll -- This is the main module of the provider. The module performs registration of the OLE DB Provider.

HHRawDataProvider.exe -- This is the module which communicates with the Hyper Historian HDA Server. The module communicates indirectly through the IcoFwxUaClient.dll library (OPC UA communication).

RawDataProviderPS.dll, RawDataProviderPS64.dll -- These files are only the proxy/stub for the HHRawDataProvider.exe module.

Data Architecture

QUERYSETTINGS table

The QUERYSETTINGS table contains information which is used during the SQL query calculation. The table has the following structure:

TAGS table

The TAGS table contains information about tags, annotations and aggregates and presents list of all tags, annotations and aggregates that are available in the Hyper Historian HDA Server. The table has the following structure:

NOTE: When browsing for a calculated Hyper Historian tag, the resulting tag will include an equal sign (=) in the name.

The format for a Hyper Historian calculated tag is hh:\Configuration\Folder:=calcTagName

This helps to determine if a particular tag (e.g., hh:\Configuration\Calc:=NoisyRamp)is a calculated tag or not. The inclusion of an equals sign (=) in the tag will confirm that it is a calculated tag.

RAWDATA table

The RAWDATA table contains information about all raw data which are in the Hyper Historian HDA Server. The table has following structure:

Since Hyper Historian V10.71, we've introduced new RAWDATA tables that expose the VALUE column in a specific data type (e.g. single or string). The tables are:

NOTE: When browsing for a calculated Hyper Historian tag, the resulting tag will include an equal sign (=) in the name.

The format for a Hyper Historian calculated tag is hh:\Configuration\Folder:=calcTagName

This helps to determine if a particular tag (e.g., hh:\Configuration\Calc:=NoisyRamp)is a calculated tag or not. The inclusion of an equals sign (=) in the tag will confirm that it is a calculated tag.

Supported SQL Constructs

SELECT query

The following SELECT syntax is supported:

SELECT [lead count restriction] expression FROM table | stored procedure [WHERE condition];

The following rules apply to individual SELECT elements:

• Expression – Defines column(s) to be retrieved by the SELECT query. These may include SQL aggregate column(s) as well. But it is not possible to combine ordinal and aggregate columns together in one SQL query (we do not support GROUP BY).

• Table | stored procedure – Defines table or stored procedure to select data from. It is not possible to combine table with stored procedure in one SQL query.

• WHERE condition – Defines logical expression that needs to evaluate to true in order to return given table row. The expression only allows AND/OR chaining, usage of brackets, and logical comparison operators (<=, <, >, =>, <>, =).

• Count restriction – Can be used to restrict number of retrieved rows. Lead restriction has form TOP x where x is number of rows to return. Note that count restrictions are applied after the query is evaluated, thus they unfortunately won’t affect performance in positive.

Be careful when you are running queries against the RAWDATA table. If the ALLOW_EMPTY_TAG in the QUERYSETTINGS table is set to ''true'', you may see the following. You can run query without the WHERE clause, but if you do so, the OLE DB Provider will get all data for all tags in the specified catalog (Logging group) and schema (Collector group). Then, the provider must sort data from all tags to one stream and this data will be sent to the output. This can take a very long time, depending on the tag count. You can set ALLOW_EMPTY_TAG to ''false''. In this case, the queries without TAGNAME in the WHERE clause will fail (such queries are not permitted).

INSERT query

The following INSERT syntax is supported:

INSERT INTO table (TAGNAME, TIMESTAMP, VALUE) VALUES (<tagname>, <timestamp>, <value>);

The INSERT query is supported only for the RAWDATA table. When you want to insert a new value, you have to specify TAGNAME, TIMESTAMP and VALUE. QUALITY is set automatically to ''good''. When you are using the SQL Server, use OPENQUERY for the INSERT.

Example:

INSERT INTO Signals.RAWDATA (TAGNAME, TIMESTAMP, VALUE) VALUES ('Sine', '2014-01-01 10:00:00', 25);

UPDATE query

The following UPDATE syntax is supported:

UPDATE table SET column_name_1 = column_value_1 [, column_name_2 = column_value_2, …] [WHERE condition];

The UPDATE query can be used only against the QUERYSETTINGS and RAWDATA table. When you are updating QUERYSETTINGS table there is no WHERE clause needed. When you are updating RAWDATA table you have to specify TAGNAME and TIMESTAMP. You can update only the VALUE. QUALITY is automatically set to good. When you are using the SQL Server, use OPENQUERY for the UPDATE.

Example for the QUERYSETTINGS table:

UPDATE QUERYSETTINGS SET MAX_ROWS_TO_RETURN = 1000';

Example for the RAWDATA table:

UPDATE Signals.RAWDATA SET VALUE = 25 WHERE TAGNAME = 'Sine' AND TIMESTAMP = '2014-01-01 10:00:00';

DELETE query

At this time, the DELETE query is not supported by the Hyper Historian SQL Query Engine.

SQL aggregates

The following standard SQL aggregates are supported in SELECT column definition expression:

• MIN

• MAX

• AVG

• SUM

• COUNT

All of these functions require column names as parameters, e.g. SELECT SUM(VALUE) FROM … . When you are using SQL aggregates, it is not possible to get other common columns. The GROUP BY clause is not supported.

SQL functions

The following are SQL functions:

QualityToStr

This function can be used instead of the QUALITY column. The function converts quality from DWORD representation (number) to the string, e.g. SELECT TAGNAME, QualityToStr(QUALITY) FROM RAWDATA … .

Output can be one of the following values:

1. • Good

   • Bad

   • Uncertain

QualityToStr2

This function can be used instead of the QUALITY column. The function converts quality from DWORD representation (number) to the string, e.g. SELECT TAGNAME, QualityToStr2(QUALITY) FROM RAWDATA … .

The difference between the QualityToStr and QualityToStr2 functions is that the QualityToStr2 function returns the exact string which corresponds to the number. E.g. 10813440 means GoodNoData or 2157838336 means BadDataUnavailable.

DataTypeToStr

This function can be used instead of the DATATYPE column. Function converts data type from the WORD representation (number) to the string, e.g.  SELECT TAGNAME, DataTypeToStr(DATATYPE) FROM TAGS … .

Output can be one of the following values:

1. • VT_BOOL

   • VT_UI1

   • VT_UI2

   • VT_UI4

   • VT_UI8

   • VT_I1

   • VT_I2

   • VT_I4

   • VT_I8

   • VT_R4

   • VT_R8

AccessRightsToStr

This function can be used instead of the ACCESSRIGHTS column. Function converts access rights from WORD representation (number) to the string, e.g. SELECT TAGNAME, AccessRightsToStr(ACCESSRIGHTS) FROM TAGS … .

Output can be one of the following values:

1. • TAG_ACCESS_RIGHTS_NONE

   • TAG_ACCESS_RIGHTS_READ

   • TAG_ACCESS_RIGHTS_WRITE

   • TAG_ACCESS_RIGHTS_READ_WRITE

IsGood, IsBad and IsUncertain

These functions can be used in WHERE clause. The IsGood() function selects only raw data where quality is good, likewise other functions, e.g. SELECT * FROM RAWDATA WHERE IsBad(QUALITY) = 1;

BitMask

Function provides bit mask operations. Supported operators are &, | and ^. Function can be used in WHERE clause, e.g. SELECT * FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' and BitMask('&', 3221225472, QUALITY) = 0;

Date/Time functions

DateAdd, Now, NowUTC

In the WHERE clause, you can use date / time functions. You can use the DateAdd() function and you can use also Now() and NowUTC() variables, e.g. SELECT * FROM RAWDATA WHERE TIMESTAMP >= DateAdd(hh, -2, NowUTC()) and TIMESTAMP <= NowUTC(); This query returns all raw data which are 2 hours old at maximum.

Function syntax is DateAdd(DATE_PART, VALUE, BASE_TIMESTAMP), where the parameters can have the following values:

·         DATE_PART

o ms – milliseconds,

o ss – seconds,

o mi – minutes,

o hh – hours,

o dd – days,

o wk – weeks,

o mm – months,

o yy – year.

·         VALUE – value can be any integer.

·         BASE_TIMESTAMP

o Now() – current local time,

o NowUTC() – current UTC time,

o or you can type your own timestamp in following format 'yyyy-mm-dd hh:mi:ss'.

LocalTimeToUTC

This function converts a local timestamp to the UTC timestamp. The function can be used in WHERE clause, e.g. SELECT * FROM Signals.RAWDATA WHERE TIMESTAMP >= LocalTimeToUTC('2014-01-01 10:00:00') and TIMESTAMP <= LocalTimeToUTC('2014-01-01 11:00:00');

UTCToLocalTime

This function converts an UTC timestamp to the local timestamp. The function can be used in SELECT clause, e.g. SELECT *, UTCToLocalTime(TIMESTAMP) FROM Signals.RAWDATA WHERE TAGNAME = 'Sine';

SQL stored procedures

All historical data aggregates calculations are provided through the stored procedures. In addition, more complex operations above raw data are also provided through the stored procedures as well.

The following is a list of all stored procedures supported at this time:

• HDA_BOOL – calculates Duration in State 0, Duration in State 1, Number of Transitions and Count aggregates for one tag.

• HDA_BOOL_5 – same functionality like HDA_BOOL but up to five tags.

• HDA_ANALOG – calculates Min, Max, Average, Time Average, Totalize Average, Interpolative, Last, Delta, Range, Total and Count aggregates for one tag.

• HDA_ANALOG_5 – same functionality like HDA_ANALOG but up to five tags.

• HDA_REDUCED_ANALOG – calculates Min, Max, Time Average and Count aggregates for one tag.

• HDA_REDUCED_ANALOG_5 – same functionality like HDA_REDUCED_ANALOG but up to five tags.

• SP_RAW_DATA – gets raw data for one tag.

• GET_MOST_RECENT_VALUE – returns most recent value, timestamp and quality for the specified tag name.

• GET_GOOD_VALUES – returns specified count of values (first N values) with good qualities in the specified time range.

• GET_BAD_VALUES – returns specified count of values (first N values) with bad qualities in the specified time range.

• GET_VALUES – returns specified count of values (first N values) with good and/or bad qualities in the specified time range.

• HDA_QUALITY – calculates DurationGood, DurationBad, PercentGood, PercentBad and WorstQuality aggregates

• HDA_QUALITY_5 – same functionality like HDA_QUALITY but for five tags.

• RAWDATA_INSERT – inserts new data into the RAWDATA table.

• RAWDATA_UPDATE – updates existing data in the RAWDATA table.

• GET_FILTERED_TAG_STATISTICS – calculates processed values for filtered data variables.

HDA_BOOL, HDA_ANALOG, HDA_REDUCED_ANALOG

The following is a list of input parameters for these functions:

• Start timestamp – start of the timestamp range,

• End timestamp – end of the timestamp range,

• Resampling period – time interval size,

• Tag name – when you specify only tag name (without catalog and schema) then the catalog and schema for the tag is taken from the stored procedure specification.

HDA_BOOL_5, HDA_ANALOG_5, HDA_REDUCED_ANALOG_5

The following is a list of input parameters for these functions:

• Start timestamp – start of the timestamp range

• End timestamp – end of the timestamp range

• Resampling period – time interval size

• Tag name 1

• Tag name 2

• Tag name 3

• Tag name 4

• Tag name 5

SP_RAWDATA

The following is a list of input parameters for this function:

• Start timestamp – start of the timestamp range,

• End timestamp – end of the timestamp range,

• Tag name – when you specify only tag name (without catalog and schema) then the catalog and schema for the tag is taken from the stored procedure specification.

GET_MOST_RECENT_VALUE

The following is a  list of input parameters for this stored procedure:

• Tag name.

GET_GOOD_VALUES, GET_BAD_VALUES, GET_VALUES

The following is a list of input parameters for these stored procedures:

• Start timestamp.

• End timestamp.

• Count.

• Tag name.

RAWDATA_INSERT, RAWDATA_UPDATE

The following is a list of input parameters for this function:

·         Tag name,

·         Timestamp,

·         Value,

·         Quality.

GET_FILTERED_TAG_STATISTICS

The following is a list of input parameters for this function:

·         Path filter – a string set of path names separated by slash character (/), names can be either fully qualified or can use wildcard characters as folder filter, path can be relative to hosting calculation,

·         Name filter – a string, data variable name filter,

·         Variable types – a string, where each character specifies single data variable type, when empty then it specifies all variable types (collected, calculated and aggregated), valid characters are: A … aggregated variables, R … collected (raw) variables, C … calculated variables,

·         Start timestamp,

·         End timestamp,

·         Maximum point names to return – specifies the maximum count of variables to process in a single call (communication parameter).

EXEC GET_FILTERED_TAG_STATISTICS 'Signals*', '*Slow', 'R', DateAdd(hh, -1, NowUTC()), NowUTC(), 10;

Historical Aggregates

Status code calculation

For aggregate values, the status code for each returned aggregate is ''good'' if the status code for all values used in the aggregate was good.

If the status code of any value used in computing the aggregate was not good, then the server uses the TreatUncertainAsBad, PercentDataBad and PercentDataGood parameter settings to determine the status code of the resulting aggregate for the interval. Some aggregates may explicitly define their own method of determining quality.

If the percentage of good values in an interval is greater than or equal to the PercentDataGood, the aggregate is considered ''good'', otherwise it is ''bad''.

Because a value can be either good or bad only (uncertain is defined as good or bad as per ''treat uncertain as bad'' setting), percentage good = 100 – percentage bad. If a percentage good(X) is in the following range percentage bad < X < percentage good, the quality of the aggregate is Uncertain_DataSubNormal.

Specifying a Connection

ICONICS Hyper Historian SQL Query Engine overrides some default pages in the Data Link Properties dialog. This is due to the fact that we don’t need all options from the default pages and, in addition, we need some special options.

The first page is a default Provider tab. You can choose any provider from the list. Our provider is called ICONICS Hyper Historian SQL Query Engine. When you double-click the Next button; the Connection tab appears.

The Connection tab (shown below) is an overridden tab and allows you to set the data source, initial catalog, and schema.

1. Specify the location of the Hyper Historian HDA Server. If this value is not specified, the localhost is used.

2. Next, you can specify an initial catalog (Logging group). This catalog is used as the default catalog when the SQL queries are executed. If the initial catalog is not specified, then the default catalog is the first catalog from the list. This list is gained from the Hyper Historian HDA Server.

3. You can also specify initial schema (Collector group). The rules are the same as for the initial catalog. A specified schema is used as the default schema when the SQL queries are executed and so on.

The third tab is the overridden Advanced tab, shown below. On this tab, you can specify default starting and ending timestamps. If the timestamps are specified, then the timestamps are used as default timestamps when the SQL queries are executed. These settings are applied when you run SQL queries against the RAWDATA table. When you specify timestamps in the SQL query in the WHERE clause, you will override the default timestamps.

When you don’t specify timestamps, then the default timestamps are generated every time when the query is started against the Hyper Historian SQL Query Engine. In this case, default timestamps are set subsequently. The ending timestamp is set to the current time. The starting timestamp is set to the current time minus three days (example: 2009-12-01 10:00:00, 2009-12-04 10:00:00).

Microsoft SQL Server Specifics

Microsoft SQL Server performs specific modifications to the queries passed to the linked server (e.g., aliasing). It also performs many auxiliary operations such as data type conversions and local functions.

Microsoft SQL Server preprocessing puts limitations on the query parameters. Namely, the Microsoft SQL Server won’t propagate time specified as absolute date, e.g. '2009-01-01 12:00:00', to the provider. Instead, you must:

• use date manipulation functions, i.e. dateadd(), getutcdate(), or

• “hack” the conversion using nested SELECT statement, e.g. select convert(datetime, '2009-01-01 12:00:00'), or

• use the OPENQUERY statement, e.g. SELECT * FROM OPENQUERY(HH2, '<SQL query>'). This solution is recommended to use in the SQL Server. Otherwise, you can fall into trouble.

MS SQL Server query execution problems

When Microsoft SQL Server decides not to send the entire query to the provider, the query can be still executed and can succeed. But rather than being processed by the provider it will be processed by Microsoft SQL Server.

The problems with this approach are:

• Performance – If a query, e.g. SELECT * FROM HH2.<catalog>.<schema>.RAWDATA WHERE TIMESTAMP >= '2009-01-01 12:00:00' AND TAGNAME = 'Sine'; is used, Micorosft SQL Server will execute SELECT * FROM HH2.<catalog>.<schema>.RAWDATA; against the provider. The provider won’t get information about the tag for which you can read the data. In this case, the provider will get all data for all tags in the specified catalog and schema (this may take a very long time) and after this, the Microsoft SQL Server will do the final filtering. If you want to forbid this, set the ALLOW_EMPTY_TAG in the QUERYSETTINGS to false. Then, queries like this will not be started.

• Runtime limitations – Certain queries are prohibited, e.g. queries without certain limit parameters. Microsoft SQL Server might inadvertently use these queries when executing subset of user-supplied query which would lead to query execution failure.

Troubleshooting

Make sure the HyperHistorian SQL Query Engine is correctly installed in the SQL Server:

1. Start Microsoft SQL Server Management Studio.

2. Go to the Server Objects -> Linked Servers.

3. You should see linked server named HH2.

4. Open window for new query.

5. Run following query: EXEC sp_catalogs HH2;.

6. If the provider is installed, you should get a list of all catalogs (HyperHistorian logging groups).

If you cannot get any data in the SQL Server:

1. Run the dcomcnfg application.

2. Select Component Services > Computers > My Computer > DCOM Config.

3. In the application list, find the ICONICS Hyper Historian Raw Data Provider.

4. Open its properties and go to the Security tab.

5. Check if there is a user under which the SQL Server is running (usually NETWORK SERVICE). This user must exist in the Launch and Activation Permissions. Also, this user must exist in the Access Permissions.

6. If the user exists in both cases, check if there is ''all allowed'' for this user.

7. Confirm all changes.

8. Open Windows Task Manager and go to the Processes tab.

9. Find the HHRawDataProvider.exe process and end the process (or you can restart the computer. This should be better).

10. If you still can’t get any data, check if the Hyper Historian HDA Server is running properly.

Examples

TAGS table

Selecting all tags:

SELECT * FROM Signals.TAGS;

Selecting tag with specified name:

SELECT * FROM Signals.TAGS WHERE TAGNAME = 'Sine';

Selecting all tags (only some columns):

SELECT TAGNAME, DATATYPE FROM Signals.TAGS;

QUERYSETTINGS tables

Selecting from the query settings table:

SELECT * FROM QUERYSETTINGS;

Updating information in the query settings table:

UPDATE QUERYSETTINGS SET MAX_ROWS_TO_RETURN = 1000, ALLOW_EMPTY_TAG = 0;

RAWDATA table

Selecting raw data (all tags, with default TIMESTAMPs):

SELECT * FROM Signals.RAWDATA;

Selecting raw data with specified TAGNAME and TIMESTAMPs:

SELECT * FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' AND TIMESTAMP >= '2014-01-01 10:00:00' AND TIMESTAMP <= '2014-01-01 12:00:00;

[For multiple selection]

One folder:

SELECT * FROM Folder1.Rawdata WHERE Tagname = "Tag"

Two folders:

SELECT * FROM Folder1.Folder2.Rawdata WHERE Tagname = "Tag"

Three folders:

SELECT * FROM Folder1.Folder2.Rawdata WHERE Tagname = "Folder3/Tag"

Four, etc. folders:

SELECT * FROM Folder1.Folder2.Rawdata WHERE Tagname = "Folder3/Folder4/Tag"

Selecting annotations:

SELECT * FROM Signals.RAWDATA WHERE TAGNAME = 'Sine:.Annotation' AND TIMESTAMP >= DateAdd(hh, -5, NowUTC()) AND TIMESTAMP <= NowUTC();

Selecting raw data using DateAdd() function:

SELECT * FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' AND TIMESTAMP >= DateAdd(hh, -5, NowUTC()) AND TIMESTAMP <= NowUTC();

Selecting raw data using QualityToStr() function:

SELECT TAGNAME, TIMESTAMP, QualityToStr(QUALITY), VALUE FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' AND TIMESTAMP >= DateAdd(hh, -5, NowUTC()) AND TIMESTAMP <= NowUTC();

Selecting raw data using IsGood() function:

SELECT * FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' AND TIMESTAMP >= DateAdd(hh, -5, NowUTC()) AND TIMESTAMP <= NowUTC() AND IsGood(QUALITY) = 1;

Selecting MAX, MIN and AVG value:

SELECT MIN(VALUE) AS min_value, MAX(VALUE) AS max_value, AVG(VALUE) AS avg_value FROM Signals.RAWDATA WHERE TAGNAME = 'Sine' AND TIMESTAMP >= '2014-01-01 10:00:00' AND TIMESTAMP <= '2014-01-01 12:00:00';

Hyper Historian Calculated Tag Format

Note that when browsing for a calculated Hyper Historian tag, the resulting tag will include an equal sign (=) in the name.

The format for a Hyper Historian calculated tag is hh:\Configuration\Folder:=calcTagName

This helps to determine if a particular tag (e.g., hh:\Configuration\Calc:=NoisyRamp)is a calculated tag or not. The inclusion of an equals sign (=) in the tag will confirm that it is a calculated tag.

Stored procedures

Running HDA_BOOL stored procedure:

EXEC Signals.HDA_BOOL '2014-01-01 10:00:00', '2014-01-01 12:00:00', 300000, 'Sine';

Running HDA_ANALOG stored procedure in SELECT query:

SELECT * FROM Signals.HDA_ANALOG('2014-01-01 10:00:00', '2014-01-01 12:00:00', 300000, 'Sine');

Examples for the SQL Server

Select rows from the RAWDATA table

SELECT * FROM OPENQUERY(HH2, 'SELECT * FROM Signals.RAWDATA WHERE TAGNAME = ''Sine'';');

Running stored procedure

SELECT * FROM OPENQUERY(HH2, 'EXEC Signals.HDA_BOOL ''2014-01-01 10:00:00'', ''2014-01-01 12:00:00'', 300000, ''Sine'';');

References

[1] – OPC Unified Architecture Specification; Part 13: Aggregates; Release Candidate; version 1.00; July 15, 2008

See Also:

SQL Query Engine Quick Start