Propellerhead recycle reverse engineered

Integrates data into a Hive target table after the data has been transformed by a customized script such as Perl or Python Invalid data is isolated in an error table and can be recycled. Integrates data into a Hive target table in truncate/insert (append) mode. This knowledge module supports wildcards (*,?). It provides options for better performance through Hive partitioning and fewer data movements. Loads data from local and HDFS files into Hive tables. Table 4-1 Oracle Data Integrator Application Adapter for Hadoop Knowledge Modules KM Name Oracle Loader for Hadoop is recommended for optimal loading into an Oracle database.

When the data has been aggregated, condensed, or processed into a smaller data set, you can load it into an Oracle database for further processing and analysis. You can also include customized procedural snippets (scripts) for processing the data. You can perform data validation (such as checking for NULLS and primary keys), and transformations (such as filtering, aggregations, set operations, and derived tables). The data source is typically in the local file system, HDFS, Hive tables, or external Hive tables.ДЄfter the data is loaded, you can validate and transform it by using HiveQL like you use SQL. When you implement a big data processing scenario, the first step is to load the data into Hadoop. Oracle Data Integrator uses Apache Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. However, when you use Oracle Data Integrator and Oracle Data Integrator Application Adapter for Hadoop, you do not need to write MapReduce jobs. Designing and implementing a MapReduce job requires expert programming knowledge. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Thus, Oracle Data Integrator Application Adapter for Hadoop is a group of knowledge modules for accessing data stored in Hadoop. An application adapter is a group of knowledge modules. Knowledge modules (KMs) contain the information needed by Oracle Data Integrator to perform a specific set of tasks against a specific technology. Loading processed data from Hadoop to an Oracle database for further processing and generating reports Performing validation and transformation of data within Hadoop Loading data into Hadoop from the local file system and HDFS Employing familiar and easy-to-use tools and preconfigured knowledge modules (KMs), the application adapter provides the following capabilities: Oracle Data Integrator (ODI) Application Adapter for Hadoop enables data integration developers to integrate and transform data easily within Hadoop using Oracle Data Integrator. Apache Hadoop is designed to handle and process data that is typically from data sources that are nonrelational and data volumes that are beyond what is handled by relational databases.

Propellerhead recycle reverse engineered