8. Managing Data Stores¶
As explained in Section 4, a data store encapsulates a unit of logically related information. Many applications will store all of their related data in one data store (although some applications may use more than one data store). It is important to keep in mind that a query and rule can operate only on one data store; thus, all information that should be queried or reasoned with in one unit should be loaded into one data store.
As explained in Section 4, a data store serves as a container for other kinds of objects:
tuple tables are data store components that store facts (see Section 9);
data sources can be registered with a data store to access external, non-RDF data (see Section 10);
OWL axioms and Datalog rules are used to specify rules of inference that are to be applied to the data loaded into the data store (see Section 6);
a dictionary keeps track of all RDF resources (i.e., IRIs, blank nodes, and literals) occurring in the facts in the data store; and
statistics modules summarize the data loaded into a data store in a way that helps query planning.
The behavior of a data store can be customized using various parameters, which are listed in Section 8.2.
8.1. Operations on Data Stores¶
The following list summarizes the operations on data stores available in the shell or via one of the available APIs.
A data store can be created on a server. To create a data store, one must specify the data store name and zero or more parameters expressed as key-value pairs. When a data store is created, a tuple table corresponding to the default graph is created automatically. Additional tuple tables corresponding to named graphs can be created later on. A newly created data store will contain all supported built-in tuple tables (see Section 9.5), but it will not contain any axioms, user-defined rules, or facts, and no data sources will be registered.
A data store can be deleted on the server. RDFox allows a data store to be deleted only if there are no active connections to the data store.
A data store can be saved to and subsequently loaded from a binary file. The file obtained in this way contains all data store content; thus, when a data store is loaded from a file, it is restored to exactly the same state as before saving. RDFox supports the following binary formats.
The ‘standard’ format stores the data in a way that is more resilient to changes in RDFox implementation. This format should be used in most cases.
The ‘raw’ format stores the data in exactly the same way as the data is stored in RAM. This format allows one to reconstruct the state of a data store exactly and is therefore useful when reporting bugs, but it is more likely to change between RDFox releases.
8.2. Data Store Parameters¶
The behavior of a data store is determined by a number of options encoded as key-value pairs. The options specified at data store creation time cannot be subsequently changed.
8.2.1. equality
¶
The equality
option determines how RDFox deals with the semantics of
equality, which is encoded using the owl:sameAs
property. This option has
the following values.
off
: There is no special handling of equality and theowl:sameAs
property is treated as just another property. This is the default if theequality
option is not specified.noUNA
: Theowl:sameAs
property is treated as equality, and the Unique Name Assumption is not used — that is, deriving an equality between two IRIs does not result in a contradiction. This is the treatment of equality in OWL 2 DL.UNA
: : Theowl:sameAs
property is treated as equality, but interpreted under UNA — that is, deriving an equality between two IRIs results in a contradiction, and only equalities between an IRI and a blank node, or between two blank nodes are allowed. Thus, if a triple of the form<IRI₁, owl:sameAs, IRI₂>
is derived, RDFox detects a clash and derives<IRI₁, rdf:type, owl:Nothing>
and<IRI₂, rdf:type, owl:Nothing>
.chase
: Theowl:sameAs
property is treated as equality with UNA, and furthermore no reflexivity axioms are derived. A data store initialized with this option does not support incremental reasoning. This option is intended to simulate the “chase” procedure commonly used in database research.
In all equality modes (i.e., all modes other than off
), distinct RDF
literals (e.g., strings, numbers, dates) are assumed to refer to distinct
objects, and so deriving an equality between the distinct literals results in a
contradiction.
Note RDFox will reject rules that use negation-as-failure or aggregation in
all equality
modes other than off
.
8.2.2. max-data-pool-size
¶
The value of the max-data-pool-size option is an integer that determines the maximum number of bytes that RDFox can use to store resource values (e.g., IRIs and strings). Specifying this option can reduce significantly the amount of virtual memory that RDFox uses per data store.
8.2.3. max-resource-capacity
¶
The value of the max-resource-capacity option is an integer that determines the maximum number of resources that can be stored in the data store. Specifying this option can reduce significantly the amount of virtual memory that RDFox uses per data store.
8.2.4. max-triple-capacity
¶
The value of the max-triple-capacity option is an integer that determines the maximum number of triples that can be stored in one named graph of a data store. Specifying this option can reduce significantly the amount of virtual memory that RDFox uses per data store.
8.2.5. init-resource-capacity
¶
The value of the init-resource-capacity
option is an integer that is used
as a hint to the data store specifying the number of resources that the store
will contain. This hint is used to initialize certain data structures to the
sizes that ensure faster importation of data. The actual number of resources
that a data store can contain is not limited by this option: RDFox will resize
the data structures as needed if this hint is exceeded.
8.2.6. init-triple-capacity
¶
The value of the init-triple-capacity
option is an integer that is used as
a hint to the data store specifying the number of triples that the store will
contain. This hint is used to initialize certain data structures to the sizes
that ensure faster importation of data. The actual number of triple that a data
store can contain is not limited by this option: RDFox will resize the data
structures as needed if this hint is exceeded.
8.2.7. import.rename-user-blank-nodes
¶
If the import.rename-user-blank-nodes
option is set to true
, then
user-defined blank nodes imported from distinct files are renamed apart during
the importation process; hence, importing data merges blank nodes according
to the RDF specification. There is no way to control the process of renaming
blank nodes, which can be problematic in some applications. Because of that,
the default value of this option is false
since this ensures that the data
is imported ‘as is’. Regardless of the state of this option, autogenerated
blank nodes (i.e., blank nodes obtained by expanding []
or (...)
in
Turtle files) are always renamed apart.
8.2.8. import.invalid-literal-policy
¶
The import.invalid-literal-policy
option governs how RDFox handles invalid
literals during import.
error
: Invalid literals in the input are treated as errors, and so files containing such literals cannot be imported. This is the default.as-string
: Invalid literals are converted to string literals during import. Moreover, for each invalid literal, a warning is emitted alerting the user to the fact that the value was converted.as-string-silent
: Invalid literals are converted to string literals during import, but without emitting a warning.
Note that this option applies only to data importation, and not to
DELETE
/INSERT
updates or queries.
8.2.9. auto-update-statistics
¶
The auto-update-statistics
option governs how RDFox manages statistics
about the data loaded into the system. RDFox uses these statistics during query
planning in order to identify an efficient plan, so query performance may be
suboptimal if the statistics are not up to date. The allowed values are as
follows.
off
: Statistics are never u[dated automatically, but they can be updated manually using thestats update
command or via one of the available APIs.balanced
: The cost of updating the statistics is balanced against the possibility of using outdated statistics. This is the default.eager
: Statistics are updated after each operation that has the potential to invalidate the statistics (e.g., importing data).
8.2.10. swrl-negation-as-failure
¶
The swrl-negation-as-failure
option determines how RDFox treats
ObjectComplementOf
class expressions in SWRL rules.
off
. SWRL rules are interpreted under the open-world assumption and SWRL rules featuringObjectComplementOf
are rejected. This is the default value.on
. SWRL rules are interpreted under the closed-world assumption, as described in Section 6.7.3.
8.2.11. persist-ds
¶
The persist-ds
option controls how RDFox persists data contained in a data
store. The option can be set to:
file
. The content of the data store will be automatically and incrementally saved to files within the server directory. The data store optionpersist-ds
can be set tofile
only if the server parameterpersist-ds
is also set tofile
.off
. The content of the data store will reside in memory only and will discarded when RDFox exits.
If the persist-ds
option is not specified for a data store then it will use
the value of the persist-ds
option specified for the server.
8.2.12. type
¶
The type
option determines the indexing strategy that RDFox uses to store
the data. The choice of the indexing strategy determines the maximum capacity
of a data store (i.e., the maximum number of resources and/or facts), its
memory footprint, the speed with which it can answer certain types of queries,
and whether a data store can be used concurrently. The following data store
types are currently supported:
seq
par-simple-nn
par-simple-nw
par-simple-ww
par-complex-nn
(default)par-complex-nw
par-complex-ww
A data store can be either sequential (seq
) or parallel (par
). A
sequential data store supports only single-threaded access, whereas a parallel
data store is able to run tasks such as materialization in parallel on multiple
threads.
The indexing scheme of a data store can be either simple
or complex
.
The simple indexing scheme uses less memory than the complex one, but it can be
less efficient at answering certain queries. In particular, to answer a triple
pattern of the form a b ?X
or ?X b a
, the simple indexing scheme will
traverse all triples where a
occurs in subject or object, whereas the
complex indexing scheme uses a hash index to identify all such triples with
constant delay (i.e., retrieving the first and every other triple requires
constant time). The simple scheme can thus be useful when queries are simple
but memory consumption is a concern, but in most cases the complex scheme
should be used.
In suffixes nn
, nw
, and ww
, the first character determines whether
the system uses 32-bit (n
for narrow) or 64-bit (w
for wide)
unsigned integers for representing resource IDs, and the second character
determines whether the system uses 32-bit (n
) or 64-bit (w
) unsigned
integers for representing triple IDs. Thus, an nw
store can contain at most
4 × 109 resources and at most 1.8 × 1019 triples.