Manage your HDFS data in MySQL with Talend

Apache HDFS (Hadoop Distributed File Systems) provides a software framework for distributed storage and processing of big data. In combination with tools such as MapReduce, Yarn, and other core modules, HDFS lets organizations build Apache Hadoop clusters of hundreds or thousands of nodes that can handle datasets of terabyte size. A robust ecosystem of other tools can take advantage of data stored in HDFS. Manage HDFS data in MySQL with Talend's suite of data integration tools.

Connecting to HDFS

To connect to HDFS, use the Component tab of the tHDFSExist component. Enter the Hadoop distribution and version, the HDFS directory, and name of the file you want to use.

Learn more about connecting to HDFS

More about integrating HDFS data

Talend has detailed documentation on how to ETL your HDFS data for a better view of the business.

Connecting to MySQL

MySQL is an open source relational database management system based on Structured Query Language.

Connect to MySQL with our native connector in a simple four-step process: Drag and drop the MySQL component from the Talend Palette onto the design workspace and set up your credentials.

Configuring a connection to a MySQL database >

Type in your login details and a few fields about your MySQL data, and you’ll be able to a lot of things with Talend:

  • Write, update, make changes, or suppress entries in a database.
  • Execute the stated SQL query on a specified MySQL database.
  • Check MySQL database rows against specific data quality patterns (regular expression) or Data Quality rules (business rule).
  • Call a MySQL database stored procedure.
  • Write a file with columns based on the defined delimiter and the MySQL or Aurora standards.
  • Obtain the primary key value of the record that was last inserted in a MySQL table by a user.

Work with your HDFS data

Computing data with Hadoop distributed file system Create a file in a defined directory, get it into and out of HDFS, store it to another local directory, and read it at the end of the Job. See how >

Get more from your HDFS data

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