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Rapidly create and deploy powerful Java applications that integrate with SAS xpt (XPORT) files data.

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Load SAS xpt Data to a Database Using Embulk


Use CData JDBC drivers with the open source ETL/ELT tool Embulk to load SAS xpt data to a database.

Embulk is an open source bulk data loader. When paired with the CData JDBC Driver for SASxpt, Embulk easily loads data from SAS xpt to any supported destination. In this article, we explain how to use the CData JDBC Driver for SASxpt in Embulk to load SAS xpt data to a MySQL dtabase.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live SAS xpt data. When you issue complex SQL queries to SAS xpt, the driver pushes supported SQL operations, like filters and aggregations, directly to SAS xpt and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Configure a JDBC Connection to SAS xpt Data

Before creating a bulk load job in Embulk, note the installation location for the JAR file for the JDBC Driver (typically C:\Program Files\CData\CData JDBC Driver for SASxpt\lib).

Embulk supports JDBC connectivity, so you can easily connect to SAS xpt and execute SQL queries. Before creating a bulk load job, create a JDBC URL for authenticating with SAS xpt.

Connecting to Local SASXpt Files

You can connect to local SASXpt file by setting the URI to a folder containing SASXpt files.

Connecting to S3 data source

You can connect to Amazon S3 source to read SASXpt files. Set the following properties to connect:

  • URI: Set this to the folder within your bucket that you would like to connect to.
  • AWSAccessKey: Set this to your AWS account access key.
  • AWSSecretKey: Set this to your AWS account secret key.
  • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

Connecting to Azure Data Lake Storage Gen2

You can connect to ADLS Gen2 to read SASXpt files. Set the following properties to connect:

  • URI: Set this to the name of the file system and the name of the folder which contacts your SASXpt files.
  • AzureAccount: Set this to the name of the Azure Data Lake storage account.
  • AzureAccessKey: Set this to our Azure DataLakeStore Gen 2 storage account access key.
  • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the SAS xpt JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.sasxpt.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a typical JDBC connection string for SAS xpt:

jdbc:sasxpt:URI=C:/folder;

Load SAS xpt Data in Embulk

After installing the CData JDBC Driver and creating a JDBC connection string, install the required Embulk plugins.

Install Embulk Input & Output Plugins

  1. Install the JDBC Input Plugin in Embulk.
    https://github.com/embulk/embulk-input-jdbc/tree/master/embulk-input-jdbc
    2. embulk gem install embulk-input-jdbc
  2. In this article, we use MySQL as the destination database. You can also choose SQL Server, PostgreSQL, or Google BigQuery as the destination using the output Plugins.
    https://github.com/embulk/embulk-output-jdbc/tree/master/embulk-output-mysql embulk gem install embulk-output-mysql

With the input and output plugins installed, we are ready to load SAS xpt data into MySQL using Embulk.

Create a Job to Load SAS xpt Data

Start by creating a config file in Embulk, using a name like sasxpt-mysql.yml.

  1. For the input plugin options, use the CData JDBC Driver for SASxpt, including the path to the driver JAR file, the driver class (e.g. cdata.jdbc.sasxpt.SASXptDriver), and the JDBC URL from above
  2. For the output plugin options, use the values and credentials for the MySQL database

Sample Config File (sasxpt-mysql.yml)

in: type: jdbc driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.sasxpt.jar driver_class: cdata.jdbc.sasxpt.SASXptDriver url: jdbc:sasxpt:URI=C:/folder; table: "SampleTable_1" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "SampleTable_1" mode: insert

After creating the file, run the Embulk job.

embulk run sasxpt-mysql.yml

After running the the Embulk job, find the Salesforce data in the MySQL table.

Load Filtered SAS xpt Data

In addition to loading data directly from a table, you can use a custom SQL query to have more granular control of the data loaded. You can also perform increment loads by setting a last updated column in a SQL WHERE clause in the query field.

in: type: jdbc driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.sasxpt.jar driver_class: cdata.jdbc.sasxpt.SASXptDriver url: jdbc:sasxpt:URI=C:/folder; query: "SELECT Id, Column1 FROM SampleTable_1 WHERE [RecordId] = 1" out: type: mysql host: localhost database: DatabaseName user: UserId password: UserPassword table: "SampleTable_1" mode: insert

More Information & Free Trial

By using CData JDBC Driver for SASxpt as a connector, Embulk can integrate SAS xpt data into your data load jobs. And with drivers for more than 200+ other enterprise sources, you can integrate any enterprise SaaS, big data, or NoSQL source as well. Download a 30-day free trial and get started today.