Introduction to SSIS Hadoop Components

What is SSIS?

SQL Server Integration Services (SSIS) is a powerful data integration tool provided by Microsoft. It allows you to extract, transform, and load (ETL) data from various sources into a destination of your choice. SSIS provides a graphical user interface (GUI) that allows you to design workflows using drag-and-drop functionality.

What is Hadoop?

Hadoop is an open-source framework designed for distributed storage and processing of large datasets across clusters of computers. It consists of the Hadoop Distributed File System (HDFS) for storage and the MapReduce programming model for processing data.

Integration of SSIS and Hadoop

SSIS provides components that enable integration with Hadoop, allowing you to extract and load data from Hadoop clusters. These components make it easy to work with Hadoop data using the familiar SSIS interface.

The SSIS Hadoop components include:

  • Hadoop File System Task: This task allows you to perform various operations on files stored in Hadoop, such as copying, deleting, and moving files.

  • Hadoop Hive Task: This task allows you to execute Hive queries against Hadoop data. Hive is a data warehouse infrastructure built on top of Hadoop that provides a high-level SQL-like query language called HiveQL.

  • Hadoop Pig Task: This task allows you to execute Pig scripts against Hadoop data. Pig is a high-level scripting language designed for processing and analyzing large datasets in Hadoop.

  • Hadoop MapReduce Task: This task allows you to execute custom MapReduce jobs against Hadoop data. MapReduce is a programming model for processing large datasets in parallel across a cluster of computers.

Example Scenario

Let's consider a scenario where we have a large dataset stored in Hadoop, and we want to extract some specific data from it and load it into a SQL Server database using SSIS.

Step 1: Create a new SSIS package

Open SQL Server Data Tools and create a new Integration Services project. Add a new package to the project.

Step 2: Add Hadoop File System Task

Drag and drop the Hadoop File System Task onto the Control Flow canvas. Double-click on the task to configure it.

In the Hadoop File System Task Editor, specify the Hadoop Connection Manager, which contains the connection details to your Hadoop cluster. Then, select the operation you want to perform, such as copying or moving files. Specify the source and destination paths accordingly.

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### Step 3: Add Data Flow Task

Drag and drop the Data Flow Task onto the Control Flow canvas. Double-click on the task to switch to the Data Flow tab.

In the Data Flow tab, add a Source component, such as the OLE DB Source, and configure it to connect to your Hadoop data source. Add any necessary transformations and a Destination component, such as the OLE DB Destination, to load the data into your SQL Server database.

### Step 4: Execute the package

Build and deploy the SSIS package to your SQL Server Integration Services catalog. Create a SQL Server Agent job to execute the package on a schedule or execute it manually.

## Conclusion

SSIS provides a seamless integration with Hadoop, allowing you to easily extract and load data from Hadoop clusters using the familiar SSIS interface. The SSIS Hadoop components provide a convenient way to work with Hadoop data and perform various operations on it. By combining the power of SSIS and Hadoop, you can efficiently process and analyze large datasets in your data integration workflows.