Prerequisites Limitations Terms Parameters Data type support Partitions and splits Performance Passthrough queries License information See also

Amazon Athena Azure Synapse connector

The Amazon Athena connector for Azure Synapse analytics enables Amazon Athena to run SQL queries on your Azure Synapse databases using JDBC.

Prerequisites

Deploy the connector to your AWS account using the Athena console or the AWS Serverless Application Repository. For more information, see Deploying a data source connector or Using the AWS Serverless Application Repository to deploy a data source connector.

Limitations

Write DDL operations are not supported.
In a multiplexer setup, the spill bucket and prefix are shared across all database instances.
Any relevant Lambda limits. For more information, see Lambda quotas in the AWS Lambda Developer Guide.
In filter conditions, you must cast the Date and Timestamp data types to the appropriate data type.
To search for negative values of type Real and Float, use the <= or >= operator.
The binary, varbinary, image, and rowversion data types are not supported.

Terms

The following terms relate to the Synapse connector.

Database instance – Any instance of a database deployed on premises, on Amazon EC2, or on Amazon RDS.
Handler – A Lambda handler that accesses your database instance. A handler can be for metadata or for data records.
Metadata handler – A Lambda handler that retrieves metadata from your database instance.
Record handler – A Lambda handler that retrieves data records from your database instance.
Composite handler – A Lambda handler that retrieves both metadata and data records from your database instance.
Property or parameter – A database property used by handlers to extract database information. You configure these properties as Lambda environment variables.
Connection String – A string of text used to establish a connection to a database instance.
Catalog – A non-AWS Glue catalog registered with Athena that is a required prefix for the connection_string property.
Multiplexing handler – A Lambda handler that can accept and use multiple database connections.

Parameters

Use the Lambda environment variables in this section to configure the Synapse connector.

Connection string

Use a JDBC connection string in the following format to connect to a database instance.


synapse://${jdbc_connection_string}

Using a multiplexing handler

You can use a multiplexer to connect to multiple database instances with a single Lambda function. Requests are routed by catalog name. Use the following classes in Lambda.

Handler	Class
Composite handler	`SynapseMuxCompositeHandler`
Metadata handler	`SynapseMuxMetadataHandler`
Record handler	`SynapseMuxRecordHandler`

Multiplexing handler parameters

Parameter	Description
`$catalog_connection_string`	Required. A database instance connection string. Prefix the environment variable with the name of the catalog used in Athena. For example, if the catalog registered with Athena is `mysynapsecatalog`, then the environment variable name is `mysynapsecatalog_connection_string`.
`default`	Required. The default connection string. This string is used when the catalog is `lambda:${AWS_LAMBDA_FUNCTION_NAME}`.

The following example properties are for a Synapse MUX Lambda function that supports two database instances: synapse1 (the default), and synapse2.

Property	Value
`default`	`synapse://jdbc:synapse://synapse1.hostname:port;databaseName=<database_name>;${secret1_name}`
`synapse_catalog1_connection_string`	`synapse://jdbc:synapse://synapse1.hostname:port;databaseName=<database_name>;${secret1_name}`
`synapse_catalog2_connection_string`	`synapse://jdbc:synapse://synapse2.hostname:port;databaseName=<database_name>;${secret2_name}`

Providing credentials

To provide a user name and password for your database in your JDBC connection string, you can use connection string properties or AWS Secrets Manager.

Connection String – A user name and password can be specified as properties in the JDBC connection string.

Important
As a security best practice, do not use hardcoded credentials in your environment variables or connection strings. For information about moving your hardcoded secrets to AWS Secrets Manager, see Move hardcoded secrets to AWS Secrets Manager in the AWS Secrets Manager User Guide.
AWS Secrets Manager – To use the Athena Federated Query feature with AWS Secrets Manager, the VPC connected to your Lambda function should have internet access or a VPC endpoint to connect to Secrets Manager.

You can put the name of a secret in AWS Secrets Manager in your JDBC connection string. The connector replaces the secret name with the username and password values from Secrets Manager.

For Amazon RDS database instances, this support is tightly integrated. If you use Amazon RDS, we highly recommend using AWS Secrets Manager and credential rotation. If your database does not use Amazon RDS, store the credentials as JSON in the following format:
```
{"username": "${username}", "password": "${password}"}
```

Example connection string with secret name

The following string has the secret name ${secret_name}.


synapse://jdbc:synapse://hostname:port;databaseName=<database_name>;${secret_name}

The connector uses the secret name to retrieve secrets and provide the user name and password, as in the following example.


synapse://jdbc:synapse://hostname:port;databaseName=<database_name>;user=<user>;password=<password>

Using a single connection handler

You can use the following single connection metadata and record handlers to connect to a single Synapse instance.

Handler type	Class
Composite handler	`SynapseCompositeHandler`
Metadata handler	`SynapseMetadataHandler`
Record handler	`SynapseRecordHandler`

Single connection handler parameters

Parameter	Description
`default`	Required. The default connection string.

The single connection handlers support one database instance and must provide a default connection string parameter. All other connection strings are ignored.

The following example property is for a single Synapse instance supported by a Lambda function.

Property	Value
`default`	`synapse://jdbc:sqlserver://hostname:port;databaseName=<database_name>;${secret_name}`

Configuring Active Directory authentication

The Amazon Athena Azure Synapse connector supports Microsoft Active Directory Authentication. Before you begin, you must configure an administrative user in the Microsoft Azure portal and then use AWS Secrets Manager to create a secret.

To set the Active Directory administrative user

Using an account that has administrative privileges, sign in to the Microsoft Azure portal at https://portal.azure.com/.
In the search box, enter Azure Synapse Analytics, and then choose Azure Synapse Analytics.
Open the menu on the left.
In the navigation pane, choose Azure Active Directory.
On the Set admin tab, set Active Directory admin to a new or existing user.
In AWS Secrets Manager, store the admin username and password credentials. For information on creating a secret in Secrets Manager, see Create an AWS Secrets Manager secret.

To view your secret in Secrets Manager

Open the Secrets Manager console at https://console.aws.amazon.com/secretsmanager/.
In the navigation pane, choose Secrets.
On the Secrets page, choose the link to your secret.
On the details page for your secret, choose Retrieve secret value.

Modifying the connection string

To enable Active Directory Authentication for the connector, modify the connection string using the following syntax:


synapse://jdbc:synapse://hostname:port;databaseName=database_name;authentication=ActiveDirectoryPassword;{secret_name}

Using ActiveDirectoryServicePrincipal

The Amazon Athena Azure Synapse connector also supports ActiveDirectoryServicePrincipal. To enable this, modify the connection string as follows.


synapse://jdbc:synapse://hostname:port;databaseName=database_name;authentication=ActiveDirectoryServicePrincipal;{secret_name}

For secret_name, specify the application or client ID as the username and the secret of a service principal identity in the password.

Spill parameters

The Lambda SDK can spill data to Amazon S3. All database instances accessed by the same Lambda function spill to the same location.

Parameter	Description
`spill_bucket`	Required. Spill bucket name.
`spill_prefix`	Required. Spill bucket key prefix.
`spill_put_request_headers`	(Optional) A JSON encoded map of request headers and values for the Amazon S3 `putObject` request that is used for spilling (for example, `{"x-amz-server-side-encryption" : "AES256"}`). For other possible headers, see PutObject in the Amazon Simple Storage Service API Reference.

Data type support

The following table shows the corresponding data types for Synapse and Apache Arrow.

Synapse	Arrow
bit	TINYINT
tinyint	SMALLINT
smallint	SMALLINT
int	INT
bigint	BIGINT
decimal	DECIMAL
numeric	FLOAT8
smallmoney	FLOAT8
money	DECIMAL
float[24]	FLOAT4
float[53]	FLOAT8
real	FLOAT4
datetime	Date(MILLISECOND)
datetime2	Date(MILLISECOND)
smalldatetime	Date(MILLISECOND)
date	Date(DAY)
time	VARCHAR
datetimeoffset	Date(MILLISECOND)
char[n]	VARCHAR
varchar[n/max]	VARCHAR
nchar[n]	VARCHAR
nvarchar[n/max]	VARCHAR

Partitions and splits

A partition is represented by a single partition column of type varchar. Synapse supports range partitioning, so partitioning is implemented by extracting the partition column and partition range from Synapse metadata tables. These range values are used to create the splits.

Performance

Selecting a subset of columns significantly slows down query runtime. The connector shows significant throttling due to concurrency.

The Athena Synapse connector performs predicate pushdown to decrease the data scanned by the query. Simple predicates and complex expressions are pushed down to the connector to reduce the amount of data scanned and decrease query execution run time.

Predicates

A predicate is an expression in the WHERE clause of a SQL query that evaluates to a Boolean value and filters rows based on multiple conditions. The Athena Synapse connector can combine these expressions and push them directly to Synapse for enhanced functionality and to reduce the amount of data scanned.

The following Athena Synapse connector operators support predicate pushdown:

Boolean: AND, OR, NOT
Equality: EQUAL, NOT_EQUAL, LESS_THAN, LESS_THAN_OR_EQUAL, GREATER_THAN, GREATER_THAN_OR_EQUAL, NULL_IF, IS_NULL
Arithmetic: ADD, SUBTRACT, MULTIPLY, DIVIDE, MODULUS, NEGATE
Other: LIKE_PATTERN, IN

Combined pushdown example

For enhanced querying capabilities, combine the pushdown types, as in the following example:


SELECT * 
FROM my_table 
WHERE col_a > 10 
    AND ((col_a + col_b) > (col_c % col_d)) 
    AND (col_e IN ('val1', 'val2', 'val3') OR col_f LIKE '%pattern%');

Passthrough queries

The Synapse connector supports passthrough queries. Passthrough queries use a table function to push your full query down to the data source for execution.

To use passthrough queries with Synapse, you can use the following syntax:


SELECT * FROM TABLE(
        system.query(
            query => 'query string'
        ))

The following example query pushes down a query to a data source in Synapse. The query selects all columns in the customer table, limiting the results to 10.


SELECT * FROM TABLE(
        system.query(
            query => 'SELECT * FROM customer LIMIT 10'
        ))

License information

By using this connector, you acknowledge the inclusion of third party components, a list of which can be found in the pom.xml file for this connector, and agree to the terms in the respective third party licenses provided in the LICENSE.txt file on GitHub.com.