Oracle Data Integrator is a transparent and heterogeneous Big Data Integration technology based on an open and lightweight ELT architecture. It runs a diverse set of workloads, including Spark, Spark Streaming and Pig transformations, to enable customers solve their most complex and time sensitive data transformation and data movement challenges. It is a core component of Oracle Data Integration solutions, integrating seamlessly with the rest of Oracle’s Data Integration and Business Application solutions
Oracle Data Integrator for Big Data provides the following benefits to customers:
- It brings expanded connectivity to various Big Data source such as Apache Kafka or Cassandra
- It decreases time to value for Big Data projects
- It provides a future proof Big Data Integration technology investment
- It streamlines and shortens the Big Data development and implementation process
Currently ODI supports
- Generation of Pig Latin transformations: users can choose Pig Latin as their transformation language and execution engine for ODI mappings. Apache Pig is a platform for analyzing large data sets in Hadoop and uses the high-level language Pig Latin for expressing data analysis programs.
- Generation of Spark and Spark Streaming transformations: ODI mappings can also generate PySpark. Apache Spark is a transformation engine for large-scale data processing. It provides fast in-memory processing of large data sets. Custom PySpark code can be added through user-defined functions or the table function component.
- Orchestration of ODI Jobs using Oozie: users have a choice between using the traditional ODI Agent or Apache Oozie as orchestration engines for jobs such as mappings, packages, scenarios, or procedures. Apache Oozie allows fully native execution on Hadoop infrastructures without installing an ODI agent for orchestration. Users can utilize Oozie tooling to schedule, manage, and monitor ODI jobs. ODI uses Oozie’s native actions to execute Hadoop processes and conditional branching logic
You can use Oracle Data Integrator to design the ‘what’ of an integration flow and assign knowledge modules to define the ‘how’ of the flow in an extensible range of mechanisms. The ‘how’ is whether it is Oracle, Teradata, Hive, Spark, Pig, etc.
Let’s configure Oracle Data Integrator for Cloudera Hadoop. You don’t need to install any components on your Hadoop Cluster. It is enough to have remote connection to manage all jobs on Hadoop.