ST-Hadoop is an extension to SpatialHadoop that provides efficient processing of Spatio-temporal data using MapReduce Hadoop framework. It provides an extendable spatio-temporal data types to be used in MapReduce jobs including STpoint and Interval. ST-Hadoop employs hierarchical multi-resolution spatio-temporal index structure within Hadoop Distributed File System (HDFS) as a mean of efficient retrieval of spatio-temporal data. The fact that time and space are crucial to the query processing influences our design to use two-level indexing of temporal and then spatial as a second level indexing. It also adds a lower-level of spatial indices in HDFS such as Grid file, R-tree, R+-tree, Quad-tree, and other. Some new InputFormats and RecordReaders are also provided to allow reading and processing spatio-temporal indexes efficiently in MapReduce jobs. ST-Hadoop shipped with two basic spatio-temporal operations that are implemented as efficient MapReduce jobs (i.e., Range query and join) which access ST-Hadoop spatio-temporal index. Developers can implement various spatio-temporal operations that run efficiently using ST-Hadoop data types, operations, and indexes.

ST-Hadoop is used in the same way as Hadoop. Data files are first loaded into HDFS and indexed using the stmanager command which builds the hierarchical spatio-temporal index structure of your choice of a specified resolution and lower level of a spatial index over the input file. Once the file is indexed, you can execute any of the spatio-temporal operations provided in ST-Hadoop such as range query and spatio-temporal similarity join. New operations will be added occasionally.

ST-Hadoop is packaged as a single jar file which contains all the required classes to run. All operations including building the index can be accessed through this jar file and it gets automatically distributed to all slave nodes by the Hadoop framework. In addition the spatial-site.xml configuration file needs to be placed in the conf directory of your Hadoop installation. This allows you to configure the cluster accordingly.

Please visit ST-Hadoop website there are few examples of how to use ST-Hadoop operations.

Advanced users and contributors might like to compile ST-Hadoop on their own machines. ST-Hadoop can be compiled via Maven. First, you need to grab your own version of the source code. You can do this through git. The source code resides on github. To clone the repository, run the following command

git clone https://github.com/lmarabi/st-hadoop.git

If you do not want to use git, you can still download it as a single archive provided by github.

Once you download the source code, you need to make sure you have any and Ivy installed on your system. Please check the installation guide of Maven if you do not have it installed.

To compile ST-Hadoop, navigate to the source code and run the command:

mvn compile

This will automatically retrieve all dependencies and compile the source code.

To build a redistribution package, run the command:

mvn assembly:assembly

This Maven command will package all classes of ST-Hadoop along with the dependent jars not included in Hadoop into an archive. This archive can be used to install ST-Hadoop on any existing Hadoop cluster.