.jserialize serializes a Java object into raw vector using
.junserialize re-constructs a Java object from its serialized
.jcache updates, retrieves or removes R-side object cache
which can be used for persistent storage of Java objects across
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serialized Java object as a raw vector
Not all Java objects support serialization, see Java documentation
for details. Note that Java serialization and serialization of R
objects are two entirely different mechanisms that cannot be
be used to access Java serialization facilities.
.jcache manipulates the R-side Java object cache associated
with a given Java reference:
Java objects do not persist across sessions, because the Java
Virtual Machine (JVM) is destroyed when R is closed. All saved Java
object references will be restored as
null references, since
the corresponding objects no longer exist (see R documentation on
serialization). However, it is possible to serialize a Java object
(if supported by the object) and store its serialized form in
R. This allows for the object to be deserialized when loaded into
another active session (but see notes below!)
R-side cache consists of a serialized form of the object as raw
vector. This cache is attached to the Java object and thus will be
saved when the Java object is saved. rJava provides an automated way
of deserializing Java references if they are
and have a cache attached. This is done on-demand basis whenever a
reference to a Java object is required.
Therefore packages can use
.jcache to provide a way of
creating Java references that persist across sessions. However, they
must be very cautious in doing so. First, make sure the serialized
form is not too big. Storing whole datasets in Java serialized form
will hog immense amounts of memory on the R side and should be
avoided. In addition, be aware that the cache is just a snapshot, it
doesn't change when the referenced Java object is modified. Hence it
is most useful only for references that are not modified outside
R. Finally, internal references to other Java objects accessible
from R are not retained (see below). Most common use of
.jcache is with Java references that point to definitions of
methods (e.g., models) and other descriptive objects which are then
used by other, active Java classes to act upon. Caching of such
active objects is not a good idea, they should be instantiated by
functions that operate on the descriptive references instead.
Important note: the serialization of Java references does NOT take into account any dependencies on the R side. Therefore if you hold a reference to a Java object in R that is also referenced by the serialized Java object on the Java side, then this relationship cannot be retained upon restore. Instead, two copies of disjoint objects will be created which can cause confusion and erroneous behavior.
The cache is attached to the reference external pointer and thus it
is shared with all copies of the same reference (even when changed
.jcast etc.), but it is independent of other
references to the object obtained separately
Also note that deserialization (even automated one) requires a
running virtual machine. Therefore you must make sure that either
.jpackage is used before any
Java references are accessed.
.jserialize returns a raw vector
.junserialize returns a Java object or
NULL if an error
occurred (currently you may use
.jcheck() to further
investigate the error)
.jcache returns the current cache (usually a raw vector) or
NULL if there is no cache.
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