Big Data For Dummies
Book image
Explore Book Buy On Amazon

Sqoop (SQL-to-Hadoop) is a big data tool that offers the capability to extract data from non-Hadoop data stores, transform the data into a form usable by Hadoop, and then load the data into HDFS. This process is called ETL, for Extract, Transform, and Load.

While getting data into Hadoop is critical for processing using MapReduce, it is also critical to get data out of Hadoop and into an external data source for use in other kinds of application. Sqoop is able to do this as well.

While it is sometimes necessary to move the data in real time, it is most often necessary to load or unload data in bulk. Like Pig, Sqoop is a command-line interpreter. You type Sqoop commands into the interpreter and they are executed one at a time. Four key features are found in Sqoop:

  • Bulk import: Sqoop can import individual tables or entire databases into HDFS. The data is stored in the native directories and files in the HDFS file system.

  • Direct input: Sqoop can import and map SQL (relational) databases directly into Hive and HBase.

  • Data interaction: Sqoop can generate Java classes so that you can interact with the data programmatically.

  • Data export: Sqoop can export data directly from HDFS into a relational database using a target table definition based on the specifics of the target database.

Sqoop works by looking at the database you want to import and selecting an appropriate import function for the source data. After it recognizes the input, it then reads the metadata for the table (or database) and creates a class definition of your input requirements.

You can force Sqoop to be very selective so that you get just the columns you are looking for before input rather than doing an entire input and then looking for your data. This can save considerable time. The actual import from the external database to HDFS is performed by a MapReduce job created behind the scenes by Sqoop.

Sqoop is an effective tool for nonprogrammers. The other important item to note is the reliance on underlying technologies like HDFS and MapReduce. You see this repeatedly throughout the element of the Hadoop ecosystem.

About This Article

This article is from the book:

About the book authors:

Judith Hurwitz is an expert in cloud computing, information management, and business strategy. Alan Nugent has extensive experience in cloud-based big data solutions. Dr. Fern Halper specializes in big data and analytics. Marcia Kaufman specializes in cloud infrastructure, information management, and analytics.

This article can be found in the category: