index GIN GIN stands for Generalized Inverted Index. It is an index structure storing a set of (key, posting list) pairs, where a posting list is a set of rows in which the key occurs. Each indexed value may contain many keys, so the same row ID may appear in multiple posting lists. It is generalized in the sense that a GIN index does not need to be aware of the operation that it accelerates. Instead, it uses custom strategies defined for particular data types. One advantage of GIN is that it allows the development of custom data types with the appropriate access methods, by an expert in the domain of the data type, rather than a database expert. This is much the same advantage as using GiST. The GIN implementation in PostgreSQL is primarily maintained by Teodor Sigaev and Oleg Bartunov. There is more information about GIN on their website. The GIN interface has a high level of abstraction, requiring the access method implementer only to implement the semantics of the data type being accessed. The GIN layer itself takes care of concurrency, logging and searching the tree structure. All it takes to get a GIN access method working is to implement four user-defined methods, which define the behavior of keys in the tree and the relationships between keys, indexed values, and indexable queries. In short, GIN combines extensibility with generality, code reuse, and a clean interface. The four methods that an index operator class for GIN must provide are: int compare(Datum a, Datum b) Compares keys (not indexed values!) and returns an integer less than zero, zero, or greater than zero, indicating whether the first key is less than, equal to, or greater than the second. Datum* extractValue(Datum inputValue, int32 *nkeys) Returns an array of keys given a value to be indexed. The number of returned keys must be stored into *nkeys. Datum* extractQuery(Datum query, int32 *nkeys, StrategyNumber n) Returns an array of keys given a value to be queried; that is, query is the value on the right-hand side of an indexable operator whose left-hand side is the indexed column. n is the strategy number of the operator within the operator class (see ). Often, extractQuery will need to consult n to determine the data type of query and the key values that need to be extracted. The number of returned keys must be stored into *nkeys. If number of keys is equal to zero then extractQuery should store 0 or -1 into *nkeys. 0 means that any row matches the query and sequence scan should be produced. -1 means nothing can satisfy query. Choice of value should be based on semantics meaning of operation with given strategy number. bool consistent(bool check[], StrategyNumber n, Datum query) Returns TRUE if the indexed value satisfies the query operator with strategy number n (or may satisfy, if the operator is marked RECHECK in the operator class). The check array has the same length as the number of keys previously returned by extractQuery for this query. Each element of the check array is TRUE if the indexed value contains the corresponding query key, ie, if (check[i] == TRUE) the i-th key of the extractQuery result array is present in the indexed value. The original query datum (not the extracted key array!) is passed in case the consistent method needs to consult it. Internally, a GIN index contains a B-tree index constructed over keys, where each key is an element of the indexed value (a member of an array, for example) and where each tuple in a leaf page is either a pointer to a B-tree over heap pointers (PT, posting tree), or a list of heap pointers (PL, posting list) if the list is small enough. Create vs insert In most cases, insertion into a GIN index is slow due to the likelihood of many keys being inserted for each value. So, for bulk insertions into a table it is advisable to drop the GIN index and recreate it after finishing bulk insertion. The primary goal of developing GIN indexes was to create support for highly scalable, full-text search in PostgreSQL, and there are often situations when a full-text search returns a very large set of results. Moreover, this often happens when the query contains very frequent words, so that the large result set is not even useful. Since reading many tuples from the disk and sorting them could take a lot of time, this is unacceptable for production. (Note that the index search itself is very fast.) To facilitate controlled execution of such queries GIN has a configurable soft upper limit on the size of the returned set, the gin_fuzzy_search_limit configuration parameter. It is set to 0 (meaning no limit) by default. If a non-zero limit is set, then the returned set is a subset of the whole result set, chosen at random. Soft means that the actual number of returned results could differ slightly from the specified limit, depending on the query and the quality of the system's random number generator. GIN doesn't support full index scans: because there are often many keys per value, each heap pointer would be returned many times, and there is no easy way to prevent this. When extractQuery returns zero keys, GIN will emit an error. Depending on the operator, a void query might match all, some, or none of the indexed values (for example, every array contains the empty array, but does not overlap the empty array), and GIN can't determine the correct answer, nor produce a full-index-scan result if it could determine that that was correct. It is not an error for extractValue to return zero keys, but in this case the indexed value will be unrepresented in the index. This is another reason why full index scan is not useful — it would miss such rows. GIN searches keys only by equality matching. This may be improved in future. The PostgreSQL source distribution includes GIN classes for one-dimensional arrays of all internal types. The following contrib modules also contain GIN operator classes: intarray Enhanced support for int4[] tsearch2 Support for inverted text indexing. This is much faster for very large, mostly-static sets of documents.