Azure SQL Database is a Platform As A Service (PAAS)
offering from Microsoft. It is really great for databases that are less than or
equal to 1 TB in size or larger databases that can be sharded (split) into smaller
ones that meet this requirement. Here are the sizing
details for both single and elastic Azure SQL Databases.
Many commercial off the shelf systems (COTS) contain modules that you can buy. For instance, a given SAP R/3 installation might have human resource, plant maintenance, material management, project systems, production planning, quality management, sales and distribution, financial accounting, asset accounting and fund management modules. It would not be uncommon for the database developer to query multiple related databases from a single database for reporting.
How can this same business requirement be solved with Azure SQL database?
Microsoft has provided the database developer with elastic database query that allows multiple databases to be accessed from a single end point. Before the release of this feature, an extract, transform and load (ETL) job would be required to duplicate the data.
This article continues with the Big Jon Investments sample database. Please
see my article on
Create Database Copy for more details on how to setup this environment.
Like most companies, the business owners have decided to change the requirements of the copied database. Instead of capturing cumulative data for the GSPC mutual fund, they only want to save off the current monthly data. A new database that leverages elastic database queries will be created to join the data into one logical view.
The image below shows the current proof of concept environment. The [PORTFOLIO-201510] database contains just October information and the [PORTFOLIO-201511] database contains both October and November information. This trend continues until the [PORTFOLIO-201609] database has 12 months of cumulative data.
How can we reduce the amount of data in
each Azure SQL Database (COPY) to one month?
One way to accomplish this goal is to write a custom DELETE statement for each database. The image below is the correct statement to leave just November data in the [PORTFOLIO-201511] database.
The syntax for querying related databases (vertical partitioning) from one Azure
SQL database using
elastic database query resembles
However, it is not!
PolyBase is a technology that accesses and combines both non-relational and relational data from within SQL Server 2016. Query results can be moved from either Hadoop or Azure blob storage to a SQL Server 2016 relational table or vice versa.
To solve our business problem, we are going to work through the following steps.
- For each database, do the following:
- Create a contained database user
- Give this user [db_owner rights].
- Create a new database.
- Create a new schema.
- Create a master encryption key.
- Create a database scoped credential.
- For each database, do the following:
- Define an external data source.
- Define an external table.
- Create one view to [UNION ALL] external tables.
The transact SQL code below creates a contained database user named [USR_CROSS_DBMS] and grants that user [db_owner] rights. Manually connect to each of the twelve databases and execute the code below.
-- -- Step 1 - Execute on all databases -- -- Remove existing user DROP USER IF EXISTS [USR_CROSS_DBMS] GO -- Create new user CREATE USER USR_CROSS_DBMS WITH PASSWORD = '4WhOjG4bgIW8w7d0', DEFAULT_SCHEMA=[ACTIVE] GO -- Add user to the database owner role EXEC sp_addrolemember N'db_owner', N'USR_CROSS_DBMS' GO
When writing code, it is import that the Transact SQL is restartable. That means
the existence of an object should be checked before creating the object. Remove
any existing objects before creating a new object.
The Transact SQL code below creates a database called [ONE-SHEET], a schema referred to as [SHD], a master encryption key and a database scoped credential designated as [CRD_CROSS_DBMS].
For more information, see the MSDN articles on CREATE MASTER KEY ENCRYPTION and CREATE DATABASE SCOPED CREDENTIAL.
-- -- Step 2 - Create new database (run from master) -- -- Delete existing database DROP DATABASE IF EXISTS [ONE-SHEET] GO -- Create new database CREATE DATABASE [ONE-SHEET] ( EDITION = 'STANDARD', SERVICE_OBJECTIVE = 'S0' ) GO -- -- Step 3 - Create new schema (run from user defined database) -- -- Delete existing schema. DROP SCHEMA IF EXISTS [SHD] GO -- Add new schema. CREATE SCHEMA [SHD] AUTHORIZATION [dbo] GO -- -- Step 4 - Create master key -- -- Drop master key IF EXISTS (SELECT * FROM sys.symmetric_keys WHERE name = '##MS_DatabaseMasterKey##') DROP MASTER KEY; -- Create master key CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'Qkmof0SV3yxReKEP'; GO -- -- Step 5 - Database Credential -- -- Drop db credential IF EXISTS(SELECT * FROM sys.database_credentials WHERE name = 'CRD_CROSS_DBMS') DROP DATABASE SCOPED CREDENTIAL CRD_CROSS_DBMS ; GO -- Create db credential CREATE DATABASE SCOPED CREDENTIAL CRD_CROSS_DBMS WITH IDENTITY = 'USR_CROSS_DBMS', SECRET = '4WhOjG4bgIW8w7d0'; GO
At this point, if you followed all the directions correctly, you should have a empty database named [ONE-SHEET]. Next, we need to work on creating external data sources for each related database.
The transact SQL code below creates an external data source for each of the twelve months. Dynamic Transact SQL will be used instead of having twelve blocks of code. We will be making sure the code is restartable by removing any existing objects before creating new ones. If you have not used the sp_executesql command before, it is really great for database management scripts that need to perform work on a dynamic number of objects.
For more information on the CREATE EXTERNAL DATA SOURCE statement, please see the following MSDN article.
-- -- Step 6A - Create 12 external data sources -- -- Variables DECLARE @VAR_NAME1 SYSNAME; DECLARE @VAR_NAME2 SYSNAME; DECLARE @VAR_DATE DATETIME; DECLARE @VAR_STMT NVARCHAR(1024); -- Starting value SET @VAR_DATE = '10-01-2015'; -- For each month WHILE (@VAR_DATE < '10-01-2016') BEGIN -- Set object names SET @VAR_NAME1 = 'SRC_PORTFOLIO_' + FORMAT(@VAR_DATE, 'yyyyMM'); SET @VAR_NAME2 = 'PORTFOLIO-' + FORMAT(@VAR_DATE, 'yyyyMM'); -- Drop external data src SET @VAR_STMT = '' + 'IF EXISTS ' + '( ' + ' SELECT * FROM sys.external_data_sources WHERE NAME = ' + CHAR(39) + @VAR_NAME1 + CHAR(39) + ') ' + 'DROP EXTERNAL DATA SOURCE [' + @VAR_NAME1 + '];'; exec sp_executesql @VAR_STMT; -- Create external data src SET @VAR_STMT = '' + 'CREATE EXTERNAL DATA SOURCE [' + @VAR_NAME1 + '] ' + 'WITH ' + '( ' + ' TYPE = RDBMS, ' + ' LOCATION = ''mssqltips16.database.windows.net'', ' + ' DATABASE_NAME = ' + CHAR(39) + @VAR_NAME2 + CHAR(39) + ', ' + ' CREDENTIAL = CRD_CROSS_DBMS' + '); '; EXEC sp_executesql @VAR_STMT; -- Increment the date SET @VAR_DATE = DATEADD(M, 1, @VAR_DATE); END
If you followed all the directions correctly, you should have twelve external data sources. See the image below for details. Next, we need to work on creating external tables for each of the data sources.
We will use Dynamic Transact SQL to create external tables for each of the months below. Unfortunately, there is no way to define a primary key using the [ST_SYMBOL] and [ST_DATE] fields. If we were using the on premise version of SQL Server, we could automatically leverage Partitioned Views to increase query performance for certain patterns.
For more information on the CREATE EXTERNAL TABLE statement, please see the following MSDN article.
The image below shows how primary key constraints are not supported with external tables.
The transact SQL code below creates an external table for each of the twelve months.
-- -- Step 6B - Create 12 external tables -- -- Variables DECLARE @VAR_NAME1 SYSNAME; DECLARE @VAR_NAME2 SYSNAME; DECLARE @VAR_DATE DATETIME; DECLARE @VAR_STMT NVARCHAR(1024); -- Starting value SET @VAR_DATE = '10-01-2015'; -- For each month WHILE (@VAR_DATE < '10-01-2016') BEGIN -- Set object names SET @VAR_NAME1 = 'STOCKS_' + FORMAT(@VAR_DATE, 'yyyyMM'); SET @VAR_NAME2 = 'SRC_PORTFOLIO_' + FORMAT(@VAR_DATE, 'yyyyMM') + ''; -- Drop external table SET @VAR_STMT = '' + 'IF EXISTS ' + '( ' + ' SELECT * FROM sys.external_tables WHERE NAME = ' + CHAR(39) + @VAR_NAME1 + CHAR(39) + ') ' + ' DROP EXTERNAL TABLE [SHD].[' + @VAR_NAME1 + '];'; exec sp_executesql @VAR_STMT; -- Create external table SET @VAR_STMT = ' ' + 'CREATE EXTERNAL TABLE [SHD].[' + @VAR_NAME1 + '] ' + '( ' + ' [ST_ID] [int] NOT NULL, ' + ' [ST_SYMBOL] [varchar](32) NOT NULL, ' + ' [ST_DATE] [date] NOT NULL, ' + ' [ST_OPEN] [real] NULL, ' + ' [ST_HIGH] [real] NULL, ' + ' [ST_LOW] [real] NULL, ' + ' [ST_CLOSE] [real] NULL, ' + ' [ST_VOLUME] [bigint] NULL, ' + ' [ST_ADJ_CLOSE] [real] NULL ' + ') ' + 'WITH ' + '( ' + ' DATA_SOURCE = ' + @VAR_NAME2 + ', ' + ' SCHEMA_NAME = ' + CHAR(39) + 'ACTIVE' + CHAR(39) + ', ' + ' OBJECT_NAME = ' + CHAR(39) + 'STOCKS' + CHAR(39) + '); '; EXEC sp_executesql @VAR_STMT; -- Increment the data SET @VAR_DATE = DATEADD(M, 1, @VAR_DATE) END
If you followed all the directions correctly, you should have twelve external tables. See the image below for details. Next, we need to create a view that combines all the tables together.
The transact SQL code below creates a view named [STOCKS] which is the UNION ALL of the twelve external tables.
-- -- Create view on all external tables -- -- Drop existing view DROP VIEW IF EXISTS [DBO].[STOCKS] GO -- Create new view CREATE VIEW [DBO].[STOCKS] AS SELECT * FROM [SHD].[STOCKS_201510] UNION ALL SELECT * FROM [SHD].[STOCKS_201511] UNION ALL SELECT * FROM [SHD].[STOCKS_201512] UNION ALL SELECT * FROM [SHD].[STOCKS_201601] UNION ALL SELECT * FROM [SHD].[STOCKS_201602] UNION ALL SELECT * FROM [SHD].[STOCKS_201603] UNION ALL SELECT * FROM [SHD].[STOCKS_201604] UNION ALL SELECT * FROM [SHD].[STOCKS_201605] UNION ALL SELECT * FROM [SHD].[STOCKS_201606] UNION ALL SELECT * FROM [SHD].[STOCKS_201607] UNION ALL SELECT * FROM [SHD].[STOCKS_201608] UNION ALL SELECT * FROM [SHD].[STOCKS_201609] GO
There can be a lot of Transact SQL coding to setup the Azure SQL database for elastic queries. In our example, we want to combine all the monthly data into one view. However, once the external table is defined, a database developer can start writing queries using both the local and external tables.
Executing Elastic Queries
Getting back to our business problem, you have been asked to pull summary data for each month for the GSPC mutual fund. The query below returns the high trading value, low trading value, average close value and the number of trading days for a given month. This query will supply the business owners with their required data.
-- -- Show summary statistics -- SELECT year(st_date) as st_year, month(st_date) as st_month, max(st_high) as st_high, min(st_low) as st_low, avg(st_close) as st_avg_close, count(*) as st_days FROM [DBO].[STOCKS] GROUP BY year(st_date), month(st_date) ORDER BY year(st_date), month(st_date) GO
The image below shows the results of the above query.
We can see that elastics query can SELECT data from multiple Azure SQL Databases
and return the results. However, on premise queries can actually INSERT, DELETE
and UPDATE data in related databases using the three part notation: database name,
schema name and table name.
Can external tables support such DML actions?
The answer to this question is not at this time! The image below shows a simple INSERT statement that fails.
Big Jon's Investments wanted to modify the proof of concept project in which
stock portfolio data was stored in a table in Azure on a daily basis. Each database
was changed to hold one month's worth of data. A parent database was created to
reference all the child databases by using external tables. A view was created to
UNION ALL the data into one object. Last but not least, an elastic database query
was used to return summary data on all of the trading days grouped by month.
Some of the current limitations of external tables is the inability to define constraints and/or apply data manipulation statements. However, this new feature closes a gap that previously existed. The database developer can now reference both local and remote tables when creating Azure SQL database queries.
If you want to learn more, check out Azure Documentation on this subject.
- Right now, we are pulling just summary data for the GSPC mutual fund. In
real life, the stock price is always changing from when the market opens at
9:30 am and closes at 4:00 pm. This pattern lends itself to a current day database
that having a large number of inserts and other day's databases that might be
queried on an ad-hoc basis. Such a pattern shows an imbalance of resource usage
across a set of sharded (horizontally partitioned) databases.
How can we implement elastic database pools for such databases?
- There are many other techniques that can be used to perform horizontal partitioning.
One technique is database sharding. Microsoft has released the Azure SQL database
elastic scale library for .NET which is a sharding solution.
How can we take advantage of the library for our own business problems?
- There are many situations in which you need to change the schema for a set
of database shards. Is there a way to perform this action without connecting
to each database to make the necessary DDL changes?
How can we take advantage of elastic database jobs for our own business problems?
Last Update: 2016-11-28
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