Reload Lucene Suggester Index - lucene

Question

How do I store and reload a Lucene suggester index?
This is how a build a Suggester index:
def buildAutoCompleteIndex(path:Path, data:List[Map[String,Any]])
:BlendedInfixSuggester = {
val directory = FSDirectory.open(path)
val autoComplete = new BlendedInfixSuggester(directory, new StandardAnalyzer())
autoComplete.build(new EntityIteratorStub())
data.map { d =>
autoComplete.add(d("text").asInstanceOf[BytesRef],
d("contexts").asInstanceOf[Set[BytesRef]],
d("weight").asInstanceOf[Long],
d("payload").asInstanceOf[BytesRef])
}
autoComplete.refresh
autoComplete
}
However, if I try to check if the index exists on, say, server restart, I get a "suggester was not built" exception.
def checkIfIndexExists(path:Path):BlendedInfixSuggester = {
val directory = FSDirectory.open(path)
val autoComplete = new BlendedInfixSuggester(directory, new StandardAnalyzer())
try {
// exception occurs here ->
if (autoComplete.lookup("a", 1, true, false).length > 0) autoComplete
else null
} catch {
case NonFatal(e) => {
println("Index does not exist, recreating at " + path)
null
}
}
}
Edit ==========================
Found this in Lucene AnalyzingInfixSuggester:
#Override
public boolean store(DataOutput in) throws IOException {
return false;
}
#Override
public boolean load(DataInput out) throws IOException {
return false;
}
Does this mean that storing-reloading of Suggester indexes cannot be done?

Answer 1

Using commit solved the problem.
def checkIfIndexExists(path:Path):BlendedInfixSuggester = {
val directory = FSDirectory.open(path)
val autoComplete = new BlendedInfixSuggester(directory, new StandardAnalyzer())
try {
if (autoComplete.getCount > 0) autoComplete
else null
} catch {
case NonFatal(e) => null
}
}
def buildAutoCompleteIndex(path:Path, data:List[Map[String,Any]])
:BlendedInfixSuggester = {
val directory = FSDirectory.open(path)
val autoComplete = new BlendedInfixSuggester(directory, new StandardAnalyzer())
// Just build a stub iterator to get started with
autoComplete.build(new EntityIteratorStub())
data.map { d =>
autoComplete.add(d("text").asInstanceOf[BytesRef],
d("contexts").asInstanceOf[Set[BytesRef]],
d("weight").asInstanceOf[Long],
d("payload").asInstanceOf[BytesRef])
}
autoComplete.refresh
autoComplete.commit
autoComplete
}