Class | Ferret::Index::IndexReader
In: | ext/r_index.c
Parent: | Object

## Summary

IndexReader is used for reading data from the index. This class is usually used directly for more advanced tasks like iterating through terms in an index, accessing term-vectors or deleting documents by document id. It is also used internally by IndexSearcher.

### Methods

[] close commit delete deleted? doc_freq field_infos field_names fields get_document get_norms_into has_deletions? latest? max_doc new norms num_docs set_norm term_count term_docs term_docs_for term_positions term_positions_for term_vector term_vectors terms terms_from tokenized_fields undelete_all version

### Public Class methods

IndexReader.new(dir) → index_reader

Create a new IndexReader. You can either pass a string path to a file-system directory or an actual Ferret::Store::Directory object. For example;

      dir = RAMDirectory.new()
      iw = IndexReader.new(dir)

      dir = FSDirectory.new("/path/to/index")
      iw = IndexReader.new(dir)

      iw = IndexReader.new("/path/to/index")

You can also create a what used to be known as a MultiReader by passing an array of IndexReader objects, Ferret::Store::Directory objects or file-system paths;

      iw = IndexReader.new([dir, dir2, dir3])

      iw = IndexReader.new([reader1, reader2, reader3])

      iw = IndexReader.new(["/path/to/index1", "/path/to/index2"])

### Public Instance methods

index_reader.get_document(doc_id) → LazyDoc
index_reader[doc_id] → LazyDoc

Retrieve a document from the index. See LazyDoc for more details on the document returned. Documents are referenced internally by document ids which are returned by the Searchers search methods.

index_reader.close → index_reader

Close the IndexReader. This method also commits any deletions made by this IndexReader. This method will be called explicitly by the garbage collector but you should call it explicitly to commit any changes as soon as possible and to close any locks held by the object to prevent locking errors.

index_reader.commit → index_reader

Commit any deletes made by this particular IndexReader to the index. This will use open a Commit lock.

index_reader.delete(doc_id) → index_reader

Delete document referenced internally by document id `doc_id`. The document_id is the number used to reference documents in the index and is returned by search methods.

index_reader.deleted?(doc_id) → bool

Returns true if the document at `doc_id` has been deleted.

index_reader.doc_freq(field, term) → integer

Return the number of documents in which the term `term` appears in the field `field`.

index_reader.field_infos → FieldInfos

Get the FieldInfos object for this IndexReader.

index_reader.fields → array of field-names

Returns an array of field names in the index. This can be used to pass to the QueryParser so that the QueryParser knows how to expand the "*" wild-card to all fields in the index. A list of field names can also be gathered from the FieldInfos object.

index_reader.fields → array of field-names

Returns an array of field names in the index. This can be used to pass to the QueryParser so that the QueryParser knows how to expand the "*" wild-card to all fields in the index. A list of field names can also be gathered from the FieldInfos object.

index_reader.get_document(doc_id) → LazyDoc
index_reader[doc_id] → LazyDoc

Retrieve a document from the index. See LazyDoc for more details on the document returned. Documents are referenced internally by document ids which are returned by the Searchers search methods.

index_reader.get_norms_into(field, buffer, offset) → buffer

Expert: Get the norm values into a string `buffer` starting at `offset`.

index_reader.has_deletions? → bool

Return true if the index has any deletions, either uncommitted by this IndexReader or committed by any other IndexReader.

index_reader.is_latest? → bool

Return true if the index version referenced by this IndexReader is the latest version of the index. If it isn‘t you should close and reopen the index to search the latest documents added to the index.

index_reader.max_doc → number

Returns 1 + the maximum document id in the index. It is the document_id that will be used by the next document added to the index. If there are no deletions, this number also refers to the number of documents in the index.

index_reader.norms(field) → string

Expert: Returns a string containing the norm values for a field. The string length will be equal to the number of documents in the index and it could have null bytes.

index_reader.num_docs → number

Returns the number of accessible (not deleted) documents in the index. This will be equal to IndexReader#max_doc if there have been no documents deleted from the index.

index_reader.set_norm(doc_id, field, val)

Expert: change the boost value for a `field` in document at `doc_id`. `val` should be an integer in the range 0..255 which corresponds to an encoded float value.

index_reader.term_count(field) → int

Same return a count of the number of terms in the field

index_reader.term_docs → TermDocEnum

Builds a TermDocEnum (term-document enumerator) for the index. You can use this object to iterate through the documents in which certain terms occur. See TermDocEnum for more info.

index_reader.term_docs_for(field, term) → TermDocEnum

Builds a TermDocEnum to iterate through the documents that contain the term `term` in the field `field`. See TermDocEnum for more info.

index_reader.term_positions → TermDocEnum

Same as IndexReader#term_docs except the TermDocEnum will also allow you to scan through the positions at which a term occurs. See TermDocEnum for more info.

index_reader.term_positions_for(field, term) → TermDocEnum

Same as IndexReader#term_docs_for(field, term) except the TermDocEnum will also allow you to scan through the positions at which a term occurs. See TermDocEnum for more info.

index_reader.term_vector(doc_id, field) → TermVector

Return the TermVector for the field `field` in the document at `doc_id` in the index. Return nil of no such term_vector exists. See TermVector.

index_reader.term_vectors(doc_id) → hash of TermVector

Return the TermVectors for the document at `doc_id` in the index. The value returned is a hash of the TermVectors for each field in the document and they are referenced by field names (as symbols).

index_reader.terms(field) → TermEnum

Returns a term enumerator which allows you to iterate through all the terms in the field `field` in the index.

index_reader.terms_from(field, term) → TermEnum

Same as IndexReader#terms(fields) except that it starts the enumerator off at term `term`.

index_reader.tokenized_fields → array of field-names

Returns an array of field names of all of the tokenized fields in the index. This can be used to pass to the QueryParser so that the QueryParser knows how to expand the "*" wild-card to all fields in the index. A list of field names can also be gathered from the FieldInfos object.

index_reader.undelete_all → index_reader

Undelete all deleted documents in the index. This is kind of like a rollback feature. Not that once an index is committed or a merge happens during index, deletions will be committed and undelete_all will have no effect on these documents.

index_reader.version → int

Returns the current version of the index reader.

[Validate]