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Note: The following description applies both to Postgres-XC and PostgreSQL if not described explicitly. You can read PostgreSQL as Postgres-XC except for version number, which is specific to each product.
Internally, a GIN index contains a B-tree index constructed over keys, where each key is an element of one or more indexed items (a member of an array, for example) and where each tuple in a leaf page contains either a pointer to a B-tree of heap pointers (a "posting tree"), or a simple list of heap pointers (a "posting list") when the list is small enough to fit into a single index tuple along with the key value.
As of PostgreSQL 9.1, null key values can be
included in the index. Also, placeholder nulls are included in the index
for indexed items that are null or contain no keys according to
extractValue. This allows searches that should find empty
items to do so.
Multicolumn GIN indexes are implemented by building a single B-tree over composite values (column number, key value). The key values for different columns can be of different types.
Note: The following description applies both to Postgres-XC and PostgreSQL if not described explicitly. You can read PostgreSQL as Postgres-XC except for version number, which is specific to each product.
Updating a GIN index tends to be slow because of the intrinsic nature of inverted indexes: inserting or updating one heap row can cause many inserts into the index (one for each key extracted from the indexed item). As of PostgreSQL 8.4, GIN is capable of postponing much of this work by inserting new tuples into a temporary, unsorted list of pending entries. When the table is vacuumed, or if the pending list becomes too large (larger than work_mem), the entries are moved to the main GIN data structure using the same bulk insert techniques used during initial index creation. This greatly improves GIN index update speed, even counting the additional vacuum overhead. Moreover the overhead work can be done by a background process instead of in foreground query processing.
The main disadvantage of this approach is that searches must scan the list of pending entries in addition to searching the regular index, and so a large list of pending entries will slow searches significantly. Another disadvantage is that, while most updates are fast, an update that causes the pending list to become "too large" will incur an immediate cleanup cycle and thus be much slower than other updates. Proper use of autovacuum can minimize both of these problems.
If consistent response time is more important than update speed, use of pending entries can be disabled by turning off the FASTUPDATE storage parameter for a GIN index. See CREATE INDEX for details.
Note: The following description applies both to Postgres-XC and PostgreSQL if not described explicitly. You can read PostgreSQL as Postgres-XC except for version number, which is specific to each product.
GIN can support "partial match" queries, in which the query
does not determine an exact match for one or more keys, but the possible
matches fall within a reasonably narrow range of key values (within the
key sorting order determined by the compare support method).
The extractQuery method, instead of returning a key value
to be matched exactly, returns a key value that is the lower bound of
the range to be searched, and sets the pmatch flag true.
The key range is then scanned using the comparePartial
method. comparePartial must return zero for a matching
index key, less than zero for a non-match that is still within the range
to be searched, or greater than zero if the index key is past the range
that could match.