Package org.apache.lucene.search.highlight

Class TokenStreamFromTermVector

  • All Implemented Interfaces:
    Closeable, AutoCloseable
    public final class TokenStreamFromTermVector
extends TokenStream
    TokenStream created from a term vector field. The term vector requires positions and/or offsets (either). If you want payloads add PayloadAttributeImpl (as you would normally) but don't assume the attribute is already added just because you know the term vector has payloads, since the first call to incrementToken() will observe if you asked for them and if not then won't get them. This TokenStream supports an efficient reset(), so there's no need to wrap with a caching impl.

    The implementation will create an array of tokens indexed by token position. As long as there aren't massive jumps in positions, this is fine. And it assumes there aren't large numbers of tokens at the same position, since it adds them to a linked-list per position in O(N^2) complexity. When there aren't positions in the term vector, it divides the startOffset by 8 to use as a temporary substitute. In that case, tokens with the same startOffset will occupy the same final position; otherwise tokens become adjacent.

    • Constructor Detail

      • TokenStreamFromTermVector

        public TokenStreamFromTermVector​(Terms vector,
                                 int maxStartOffset)
                          throws IOException
        Constructor. The uninversion doesn't happen here; it's delayed till the first call to incrementToken.
        Parameters:
        vector - Terms that contains the data for creating the TokenStream. Must have positions and/or offsets.
        maxStartOffset - if a token's start offset exceeds this then the token is not added. -1 disables the limit.
        Throws:
        IOException

    • Method Detail

      • getTermVectorTerms

        public Terms getTermVectorTerms()

      • reset

        public void reset()
           throws IOException
        Description copied from class: TokenStream
        This method is called by a consumer before it begins consumption using TokenStream.incrementToken().

        Resets this stream to a clean state. Stateful implementations must implement this method so that they can be reused, just as if they had been created fresh.

        If you override this method, always call super.reset(), otherwise some internal state will not be correctly reset (e.g., Tokenizer will throw IllegalStateException on further usage).

        Overrides:
        reset in class TokenStream
        Throws:
        IOException

      • incrementToken

        public boolean incrementToken()
                       throws IOException
        Description copied from class: TokenStream
        Consumers (i.e., IndexWriter) use this method to advance the stream to the next token. Implementing classes must implement this method and update the appropriate AttributeImpls with the attributes of the next token.

        The producer must make no assumptions about the attributes after the method has been returned: the caller may arbitrarily change it. If the producer needs to preserve the state for subsequent calls, it can use AttributeSource.captureState() to create a copy of the current attribute state.

        This method is called for every token of a document, so an efficient implementation is crucial for good performance. To avoid calls to AttributeSource.addAttribute(Class) and AttributeSource.getAttribute(Class), references to all AttributeImpls that this stream uses should be retrieved during instantiation.

        To ensure that filters and consumers know which attributes are available, the attributes must be added during instantiation. Filters and consumers are not required to check for availability of attributes in TokenStream.incrementToken().

        Specified by:
        incrementToken in class TokenStream
        Returns:
        false for end of stream; true otherwise
        Throws:
        IOException