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Introduction to Apache Gora
Transcript of Introduction to Apache Gora
The Apache Gora open source framework provides an in-memory data model and persistence for big data. Gora supports persisting to column stores, key value stores, document stores and RDBMSs, and analyzing the data with extensive Apache Hadoop™ MapReduce support. Gora uses the Apache Software License v2.0.
How do you use it?
A piece of cake...
Model your objects as an
for your datastore
Define some trivial name/value properties in
Generate persistent data beans via the GoraCompiler
Then you consume the
within your client code and begin mapping data to/between Gora-supported datastores.
Although there are various excellent ORM frameworks for relational databases, data modeling in NoSQL data stores differ profoundly from their relational cousins. Moreover, data-model agnostic frameworks such as JDO are not sufficient for use cases, where one needs to use the full power of the data models in column stores. Gora fills this gap.
Simple... to become the standard data representation and persistence framework for big data.
: Persisting objects to Column stores such as Apache HBase™, Apache Cassandra™, Hypertable; key-value stores such as Voldermort, Redis, etc; flat files in local file system of Hadoop HDFS;
: An easy to use Java-friendly common API for accessing the data regardless of its location;
: Persisting objects to Apache Lucene and Apache Solr indexes, accessing/querying the data with Gora API;
: Accesing the data and making analysis through adapters for Apache Pig, Apache Hive and Cascading;
: Out-of-the-box and extensive MapReduce (Apache Hadoop™) support for data in the data store
XML Mapping File (HBase)
Generated persistent data beans
(although also tested with 1.X)
1.2.1 & 2.5.2