Monday, 23 October 2017

Use PolyBase to read Data Lake in Azure SQL DW

Case
I have a file in an Azure Data Lake Store (ADLS) folder which I want to use in my Azure SQL Data Warehouse. In a previous blog post you used PolyBase to get the data from an Azure Blob Storage container via its access keys. How can I use PolyBase to get the data from ADLS and push the content of that file to Azure SQL DW?
Azure SQL Data Warehouse - PolyBase on ADLS















Solution
In the previous blog post we showed how to read that file from an Azure Blob Storage container via its access keys using PolyBase. However ADLS does not work with those keys, but uses the Azure Active Directory to provide access. To get authorization via Azure Active Directory we need to register a 'Web app / API'  application in Azure Active Directory that does the authorization for us. That sounds very difficult and the documentation on MSDN is not very helpful, but in the end it was quite easy.

a) Starting point
The starting point of this blog post is a file in an ADLS folder called 'mySubFolder'. The file was created in a previous blog post about U-SQL that can quickly process large amounts of data files in Azure Data Lake Analytics (ADLA). The name of our ADLS is 'bitools'.
Starting point: CSV file in ADLS
The content of the CSV file
























a1) App registrations
Go to the Azure portal and search for Azure Active Directory in the search box located in the header. This will bring you to the Azure Active Directory from your subscription. Then click on App registrations in the menu. It will show a list of all existing registrations. Next step is to click on New application registration to create a new registration for our data lake.
New application registration














a2) New application registration
Enter a new descriptive name like 'Data Lake bitools' so you will know where it is used for. Choose 'Web app / API' as Application type and then you need to enter a URL. Since we are not using the Sign-on URL property (we use the Azure sign-on), you can just enter any url like 'https://microsoft-bitools.blogspot.com'. When complete click on the Create button.
New application registration

























a3) Edit application registration - Application ID
Now search your newly created Application registration to get its Application ID. Copy that to a notepad (we need it later on). You can also edit additional properties like giving it a custom logo to make it more recognizable if you have an extensive list of app registrations.
Copy Application ID

















a4) Edit application registration - Keys
Continue editing and click on Keys in the menu to create a new access key. Give it a suitable name and expirationperiod. After clicking Save make sure to copy the generated key to the same notepad as before since you can only get it once! If you lose it you have to delete and recreate it.
Create new key










a5) Active Directory ID
Now go back to your Azure Active Directory to copy the Directory ID. You can find it when you click on Properties in the menu. Copy this ID to the same notepad that now should contain three values (ApplicationID, generated key and DirectoryID).
Get Directory ID






















a6) Setting access root folder
Go to your ADLS and click on Data Explorer. You are now in the root of your ADLS. Click on Access and then on Add to assign new permissions. Search for your Registered Application called 'bitools'. Then select it and click on the Select button. In the root folder we only need Execute permissions. 'Add to' should stay on 'This folder' and 'Add as' should stay on 'An access permission entry'. Click on the Ok button to confirm.
Setting permissions on root folder










If you forget to give Execute permissions to the root folder you will get an error when adding an external table later on:
EXTERNAL TABLE access failed due to internal error: 'Java exception raised on call to HdfsBridge_IsDirExist. Java exception message:
GETFILESTATUS failed with error 0x83090aa2 (Forbidden. ACL verification failed. Either the resource does not exist or the user is not authorized to perform the requested operation.).
[dbd91a77-1b0a-4f11-9710-d7c1b6b05268][2017-10-21T12:26:47.7748687-07:00]: Error [GETFILESTATUS failed with error 0x83090aa2 (Forbidden. ACL verification failed. Either the resource does not exist or the user is not authorized to perform the requested operation.).
[dbd91a77-1b0a-4f11-9710-d7c1b6b05268][2017-10-21T12:26:47.7748687-07:00]] occurred while accessing external file.'


a7) Setting access sub folder
Now we have to repeat this for our subfolder called 'mySubFolder'. Click on the folder and you should see the source file. Click on Access and then on Add to assign new permissions. Search for your Registered Application called 'bitools'. Then select it and click on the Select button. In this sub folder we need Read and Execute permissions. 'Add to' should be changed to on 'This folder and all children' and 'Add as' should stay on 'An access permission entry'. Click on the Ok button to confirm.
Setting permissions on sub folder










An alternative could be to give the bitools app read and execute rights on the root including all children. That saves you one step, but is less secure if you use your Data Lake for multiple purposes.


b) SSMS
Now its time to start with the actual PolyBase code, but before we start make sure your Azure SQL Data Warehouse is started and use SQL Server Management Studio (SSMS) to connect to your Data Warehouse. Notice that the icon of a SQL DW is different than SQL DB.
Icon SQL DW vs SQL DB
















b1) Master key
In the next step we will use a credential that points to the registered application. To encrypt that credential, we first need to create a master key in our Azure SQL Data Warehouse, but only if you do not already have one. You can check that in the table sys.symmetric_keys. If a row exists where the symmetric_key_id column is 101 (or the name column is '##MS_DatabaseMasterKey##') then you already have a master key. Else we need to create one. For Azure SQL Data Warehouse a masterkey password is optional. For this example we will not use the password.
--Master key
IF NOT EXISTS (SELECT * FROM sys.symmetric_keys WHERE symmetric_key_id = 101)
BEGIN
    PRINT 'Creating Master Key'
    CREATE MASTER KEY;
END
ELSE
BEGIN
    PRINT 'Master Key already exists'
END 

b2) Credentials
Next step is to create a credential which will be used to access the subfolder in ADLS. For this you need the ID's and key from the notepad. The IDENTITY has the following format:
[ApplicationID]@https://login.windows.net/[DirectoryID]/oauth2/token
Replace ApplicationID (including the square brackets) with the ID from step a3 and DirectoryID (including the square brackets) with the ID from a5. The SECRET should be filled with the key from step a4. After setting the correct ID's and key, execute the following code:
--Credential
CREATE DATABASE SCOPED CREDENTIAL bitools_user
WITH
    IDENTITY = 'aaf0ab52-560e-40b1-b4df-caac1f0e5376@https://login.windows.net/3xxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxb/oauth2/token',
    SECRET = '6LUnE4shZ4p1jUhj7/fkLH03yfbSxi2WRWre9c0yVTs=';
;

Tip:
Give the credential a descriptive name so that you know where it is used for. You can find all credentials in the table sys.database_credentials:
--Find all credential
SELECT * FROM sys.database_credentials

b3) External data source
With the credential from the previous step we will create an External data source that points to the ADLS folder where your file is located. Execute the code below where:
  • TYPE = HADOOP (because PolyBase uses the Hadoop APIs to access the container)
  • LOCATION = the connection string to ADLS (replace 'bitools' with the name of your own ADLS name).
  • CREDENTIAL = the name of the credentials created in the previous step.
--Create External Data Source
CREATE EXTERNAL DATA SOURCE AzureDataLakeStore
WITH (
TYPE = HADOOP,
LOCATION = 'adl://bitools.azuredatalakestore.net',
CREDENTIAL = bitools_user
);

Tip:
Give the external source a descriptive name so that you know where it is used for. You can find all external data sources in the table sys.external_data_sources:
--Find all external sources
SELECT * FROM sys.external_data_sources

Notice that the filename or subfolder is not mentioned in the External Data Source. This is done in the External Table. This allows you to use multiple files from the same folder as External Tables.


b4) External File format
Now we need to describe the format used in the source file. In our case we have a comma delimited file. You can also use this file format to supply the date format, compression type or encoding.
--Create External Data Source
CREATE EXTERNAL FILE FORMAT TextFile
WITH (
    FORMAT_TYPE = DelimitedText,
    FORMAT_OPTIONS (FIELD_TERMINATOR = ',')
);

Tip:
Give the format a descriptive name so that you know where it is used for. You can find all external file formats in the table sys.external_file_formats:
--Find all external file formats
SELECT * FROM sys.external_file_formats

b5) External Table
The last step before we can start quering, is creating the external table. In this create table script you need to specify all columns, datatypes and the filename that you want to read. The filename starts with a forward slash. You also need the datasource from step 3 and the file format from step 4.
--Create External table
CREATE EXTERNAL TABLE dbo.sensordata (
    [Date] DateTime2(7) NOT NULL,
    [temp] INT NOT NULL,
    [hmdt] INT NOT NULL,
    [location] nvarchar(50) NOT NULL
)
WITH (
    LOCATION='/mySubFolder/bitools_sample_data_AveragePerDayPerBuilding.csv',
    DATA_SOURCE=AzureDataLakeStore, -- from step 3
    FILE_FORMAT=TextFile            -- from step 4
);
Note:
PolyBase does not like columnname headers. It will handle it like a regular data row an throw an error when the datatype doesn't match. There is a little workaround for this with REJECT_TYPE and REJECT_VALUE. However this only works when the datatype of the header is different than the datatypes of the actual rows. Else you have to filter the header row in a subsequent step.
--Create External table with header
CREATE EXTERNAL TABLE dbo.sensordata5 (
    [Date] DateTime2(7) NOT NULL,
    [temp] INT NOT NULL,
    [hmdt] INT NOT NULL,
    [location] nvarchar(50) NOT NULL
)
WITH (
    LOCATION='/mySubFolder/bitools_sample_data_AveragePerDayPerBuilding.csv',
    DATA_SOURCE=AzureDataLakeStore,
    FILE_FORMAT=TextFile,
    REJECT_TYPE = VALUE, -- Reject rows with wrong datatypes
    REJECT_VALUE = 1     -- Allow 1 failure (the header)
);
You can find all external tables in the table sys.external_tables.
--Find all external tables
SELECT * FROM sys.external_tables
However you can also find the External Table (/the External Data Source/the External File Format) in the Object Explorer of SSMS.
SSMS Object Explorer
























b6) Query external table
Now you can query the external table like any other regular table. However the table is read-only so you can not delete, update or insert records. If you update the source file then the data in this external table also changes instantly because the file is used to get the data.
--Testing
SELECT count(*) FROM dbo.sensordata;
SELECT * FROM dbo.sensordata;
Quering an external table
























b7) What is next?
Most likely you will be using a CTAS query (Create Table As Select) to copy and transform the data to an other table since this is the fasted/preferred way in SQL DW. In a subsequent post we will explain more about CTAS, but here is how a CTAS query looks like.
--CTAS
CREATE TABLE [dbo].[Buildings]
WITH
(
    DISTRIBUTION = ROUND_ROBIN
,   CLUSTERED COLUMNSTORE INDEX
)
AS
SELECT  [location]
,       [date]
,       [temp]
,       [hmdt]
FROM    [dbo].[sensordata]
;

In some cases you could also use an SELECT INTO query as an alternative for CTAS.

Summary
In this post you saw how easy it was to read a file from the Azure Data Lake Store and use it as a table in Azure SQL Data Warehouse. Although it did required some extra steps compared to PolyBase on an Azure Blob Storage. Jhon Masschelein (B|L|T) has a very helpful post about this matter.

In an other post we will explain the basic usage of the CTAS query which is the preferred way to handle large sets of data in Azure SQL DW and in its on-premises precursor APS (a.k.a. PDW).

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