TDB/JavaAPI

From Jena wiki

All the operations of the Jena API including the SPARQL query support. The application obtains a model or RDF datasets from TDB then uses it as for any other model or dataset.

Contents 1 Constructing a model or dataset 1.1 Using a directory name 1.2 Using an assembler file 2 Bulkloader 3 Caching and synchronization

[edit] Constructing a model or dataset

The class TDBFactory contains the static factory methods for creating and connecting to a TDB-backed graph or an RDF dataset. Models and datasets should be closed after use.

See also the examples in src-examples.

An application can specify the model or dataset by:

1. Giving a directory name
2. Giving an assembler file

If a directory is empty, the TDB files for indexes and node table are created. If the directory contains files from a previous application run, TDB connects to the data already there.

[edit] Using a directory name

  // Direct way: Make a TDB-backed Jena model in the named directory.
  String directory = "MyDatabases/DB1" ;
  Model model = TDBFactory.createModel(directory) ;
  ...
  model.close() ;

  // Direct way: Make a TDB-backed dataset
  String directory = "MyDatabases/Dataset1" ;
  Dataset dataset = TDBFactory.createDataset(directory) ;
  ...
  dataset.close() ;

[edit] Using an assembler file

  // Assembler way: Make a TDB-back Jena model in the named directory.
  // This way, you can change the model being used without changing the code.
  // The assembler file is a configuration file.
  // The same assembler description will work in Joseki. 
  String assemblerFile = "Store/tdb-assembler.ttl" ;
  Model model = TDBFactory.assembleModel(assemblerFile) ;
  ...
  model.close() ;

  String assemblerFile = "Store/tdb-assembler.ttl" ;
  Dataset dataset = TDBFactory.assembleDataset(assemblerFile) ;
  ...
  dataset.close() ;

See the TDB assembler documentation for details.

[edit] Bulkloader

The bulkloader is a faster way to load data into an empty graph than just using the Jena update operations.

It is accessed through the command line utility tdbloader.

[edit] Caching and synchronization

TDB employs caching at various levels, from RDF terms to disk blocks. It is important to flush all caches to make the file state consistent with the cached states because some caches are write-behind so unwritten chnages may be held in-memory.

Caches are flushes when a model or dataset is closed.

 Model model = TDBFactory.createModel(disk location) ;
 ...
 model.close() ;

 Dataset dataset = TDBFactory.createDataset(disk location) ;
 ...
 dataset .close() ;

In addition, while TDB does not support full transaction semantics, the Model.commit does provide for synchronising the in-memory and disk states.

 model.commit() ;

TDB provides an explicit call for model and dataset objects for synchronization with disk:

  Model model = ... ;
  TDB.sync(model) ;
       
  Dataset dataset = ...  ;
  TDB.sync(dataset ) ;

Any dataset or model can be passed to these functions - if they are not backed by TDB then no action is taken and the call merely returns without error.