Traditionally, implementing a new index access method meant a lot of difficult work. It was necessary to understand the inner workings of the database, such as the lock manager and Write-Ahead Log. The GiST interface has a high level of abstraction, requiring the access method implementer only to implement the semantics of the data type being accessed. The GiST layer itself takes care of concurrency, logging and searching the tree structure.
This extensibility should not be confused with the extensibility of the
other standard search trees in terms of the data they can handle. For
example, PostgreSQL supports extensible B-trees
and hash indexes. That means that you can use
PostgreSQL to build a B-tree or hash over any
data type you want. But B-trees only support range predicates
(<
, =
, >
),
and hash indexes only support equality queries.
So if you index, say, an image collection with a PostgreSQL B-tree, you can only issue queries such as “is imagex equal to imagey”, “is imagex less than imagey” and “is imagex greater than imagey”. Depending on how you define “equals”, “less than” and “greater than” in this context, this could be useful. However, by using a GiST based index, you could create ways to ask domain-specific questions, perhaps “find all images of horses” or “find all over-exposed images”.
All it takes to get a GiST access method up and running is to implement several user-defined methods, which define the behavior of keys in the tree. Of course these methods have to be pretty fancy to support fancy queries, but for all the standard queries (B-trees, R-trees, etc.) they're relatively straightforward. In short, GiST combines extensibility along with generality, code reuse, and a clean interface.
There are five methods that an index operator class for
GiST must provide, and four that are optional.
Correctness of the index is ensured
by proper implementation of the same
, consistent
and union
methods, while efficiency (size and speed) of the
index will depend on the penalty
and picksplit
methods.
Two optional methods are compress
and
decompress
, which allow an index to have internal tree data of
a different type than the data it indexes. The leaves are to be of the
indexed data type, while the other tree nodes can be of any C struct (but
you still have to follow PostgreSQL data type rules here,
see about varlena
for variable sized data). If the tree's
internal data type exists at the SQL level, the STORAGE
option
of the CREATE OPERATOR CLASS
command can be used.
The optional eighth method is distance
, which is needed
if the operator class wishes to support ordered scans (nearest-neighbor
searches). The optional ninth method fetch
is needed if the
operator class wishes to support index-only scans, except when the
compress
method is omitted.
consistent
Given an index entry p
and a query value q
,
this function determines whether the index entry is
“consistent” with the query; that is, could the predicate
“indexed_column
indexable_operator
q
” be true for
any row represented by the index entry? For a leaf index entry this is
equivalent to testing the indexable condition, while for an internal
tree node this determines whether it is necessary to scan the subtree
of the index represented by the tree node. When the result is
true
, a recheck
flag must also be returned.
This indicates whether the predicate is certainly true or only possibly
true. If recheck
= false
then the index has
tested the predicate condition exactly, whereas if recheck
= true
the row is only a candidate match. In that case the
system will automatically evaluate the
indexable_operator
against the actual row value to see
if it is really a match. This convention allows
GiST to support both lossless and lossy index
structures.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_consistent(internal, data_type, smallint, oid, internal) RETURNS bool AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_consistent); Datum my_consistent(PG_FUNCTION_ARGS) { GISTENTRY *entry = (GISTENTRY *) PG_GETARG_POINTER(0); data_type *query = PG_GETARG_DATA_TYPE_P(1); StrategyNumber strategy = (StrategyNumber) PG_GETARG_UINT16(2); /* Oid subtype = PG_GETARG_OID(3); */ bool *recheck = (bool *) PG_GETARG_POINTER(4); data_type *key = DatumGetDataType(entry->key); bool retval; /* * determine return value as a function of strategy, key and query. * * Use GIST_LEAF(entry) to know where you're called in the index tree, * which comes handy when supporting the = operator for example (you could * check for non empty union() in non-leaf nodes and equality in leaf * nodes). */ *recheck = true; /* or false if check is exact */ PG_RETURN_BOOL(retval); }
Here, key
is an element in the index and query
the value being looked up in the index. The StrategyNumber
parameter indicates which operator of your operator class is being
applied — it matches one of the operator numbers in the
CREATE OPERATOR CLASS
command.
Depending on which operators you have included in the class, the data
type of query
could vary with the operator, since it will
be whatever type is on the righthand side of the operator, which might
be different from the indexed data type appearing on the lefthand side.
(The above code skeleton assumes that only one type is possible; if
not, fetching the query
argument value would have to depend
on the operator.) It is recommended that the SQL declaration of
the consistent
function use the opclass's indexed data
type for the query
argument, even though the actual type
might be something else depending on the operator.
union
This method consolidates information in the tree. Given a set of entries, this function generates a new index entry that represents all the given entries.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_union(internal, internal) RETURNS storage_type AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_union); Datum my_union(PG_FUNCTION_ARGS) { GistEntryVector *entryvec = (GistEntryVector *) PG_GETARG_POINTER(0); GISTENTRY *ent = entryvec->vector; data_type *out, *tmp, *old; int numranges, i = 0; numranges = entryvec->n; tmp = DatumGetDataType(ent[0].key); out = tmp; if (numranges == 1) { out = data_type_deep_copy(tmp); PG_RETURN_DATA_TYPE_P(out); } for (i = 1; i < numranges; i++) { old = out; tmp = DatumGetDataType(ent[i].key); out = my_union_implementation(out, tmp); } PG_RETURN_DATA_TYPE_P(out); }
As you can see, in this skeleton we're dealing with a data type
where union(X, Y, Z) = union(union(X, Y), Z)
. It's easy
enough to support data types where this is not the case, by
implementing the proper union algorithm in this
GiST support method.
The result of the union
function must be a value of the
index's storage type, whatever that is (it might or might not be
different from the indexed column's type). The union
function should return a pointer to newly palloc()
ed
memory. You can't just return the input value as-is, even if there is
no type change.
As shown above, the union
function's
first internal
argument is actually
a GistEntryVector
pointer. The second argument is a
pointer to an integer variable, which can be ignored. (It used to be
required that the union
function store the size of its
result value into that variable, but this is no longer necessary.)
compress
Converts a data item into a format suitable for physical storage in
an index page.
If the compress
method is omitted, data items are stored
in the index without modification.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_compress(internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_compress); Datum my_compress(PG_FUNCTION_ARGS) { GISTENTRY *entry = (GISTENTRY *) PG_GETARG_POINTER(0); GISTENTRY *retval; if (entry->leafkey) { /* replace entry->key with a compressed version */ compressed_data_type *compressed_data = palloc(sizeof(compressed_data_type)); /* fill *compressed_data from entry->key ... */ retval = palloc(sizeof(GISTENTRY)); gistentryinit(*retval, PointerGetDatum(compressed_data), entry->rel, entry->page, entry->offset, FALSE); } else { /* typically we needn't do anything with non-leaf entries */ retval = entry; } PG_RETURN_POINTER(retval); }
You have to adapt compressed_data_type
to the specific
type you're converting to in order to compress your leaf nodes, of
course.
decompress
Converts the stored representation of a data item into a format that
can be manipulated by the other GiST methods in the operator class.
If the decompress
method is omitted, it is assumed that
the other GiST methods can work directly on the stored data format.
(decompress
is not necessarily the reverse of
the compress
method; in particular,
if compress
is lossy then it's impossible
for decompress
to exactly reconstruct the original
data. decompress
is not necessarily equivalent
to fetch
, either, since the other GiST methods might not
require full reconstruction of the data.)
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_decompress(internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_decompress); Datum my_decompress(PG_FUNCTION_ARGS) { PG_RETURN_POINTER(PG_GETARG_POINTER(0)); }
The above skeleton is suitable for the case where no decompression is needed. (But, of course, omitting the method altogether is even easier, and is recommended in such cases.)
penalty
Returns a value indicating the “cost” of inserting the new
entry into a particular branch of the tree. Items will be inserted
down the path of least penalty
in the tree.
Values returned by penalty
should be non-negative.
If a negative value is returned, it will be treated as zero.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_penalty(internal, internal, internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT; -- in some cases penalty functions need not be strict
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_penalty); Datum my_penalty(PG_FUNCTION_ARGS) { GISTENTRY *origentry = (GISTENTRY *) PG_GETARG_POINTER(0); GISTENTRY *newentry = (GISTENTRY *) PG_GETARG_POINTER(1); float *penalty = (float *) PG_GETARG_POINTER(2); data_type *orig = DatumGetDataType(origentry->key); data_type *new = DatumGetDataType(newentry->key); *penalty = my_penalty_implementation(orig, new); PG_RETURN_POINTER(penalty); }
For historical reasons, the penalty
function doesn't
just return a float
result; instead it has to store the value
at the location indicated by the third argument. The return
value per se is ignored, though it's conventional to pass back the
address of that argument.
The penalty
function is crucial to good performance of
the index. It'll get used at insertion time to determine which branch
to follow when choosing where to add the new entry in the tree. At
query time, the more balanced the index, the quicker the lookup.
picksplit
When an index page split is necessary, this function decides which entries on the page are to stay on the old page, and which are to move to the new page.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_picksplit(internal, internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_picksplit); Datum my_picksplit(PG_FUNCTION_ARGS) { GistEntryVector *entryvec = (GistEntryVector *) PG_GETARG_POINTER(0); GIST_SPLITVEC *v = (GIST_SPLITVEC *) PG_GETARG_POINTER(1); OffsetNumber maxoff = entryvec->n - 1; GISTENTRY *ent = entryvec->vector; int i, nbytes; OffsetNumber *left, *right; data_type *tmp_union; data_type *unionL; data_type *unionR; GISTENTRY **raw_entryvec; maxoff = entryvec->n - 1; nbytes = (maxoff + 1) * sizeof(OffsetNumber); v->spl_left = (OffsetNumber *) palloc(nbytes); left = v->spl_left; v->spl_nleft = 0; v->spl_right = (OffsetNumber *) palloc(nbytes); right = v->spl_right; v->spl_nright = 0; unionL = NULL; unionR = NULL; /* Initialize the raw entry vector. */ raw_entryvec = (GISTENTRY **) malloc(entryvec->n * sizeof(void *)); for (i = FirstOffsetNumber; i <= maxoff; i = OffsetNumberNext(i)) raw_entryvec[i] = &(entryvec->vector[i]); for (i = FirstOffsetNumber; i <= maxoff; i = OffsetNumberNext(i)) { int real_index = raw_entryvec[i] - entryvec->vector; tmp_union = DatumGetDataType(entryvec->vector[real_index].key); Assert(tmp_union != NULL); /* * Choose where to put the index entries and update unionL and unionR * accordingly. Append the entries to either v_spl_left or * v_spl_right, and care about the counters. */ if (my_choice_is_left(unionL, curl, unionR, curr)) { if (unionL == NULL) unionL = tmp_union; else unionL = my_union_implementation(unionL, tmp_union); *left = real_index; ++left; ++(v->spl_nleft); } else { /* * Same on the right */ } } v->spl_ldatum = DataTypeGetDatum(unionL); v->spl_rdatum = DataTypeGetDatum(unionR); PG_RETURN_POINTER(v); }
Notice that the picksplit
function's result is delivered
by modifying the passed-in v
structure. The return
value per se is ignored, though it's conventional to pass back the
address of v
.
Like penalty
, the picksplit
function
is crucial to good performance of the index. Designing suitable
penalty
and picksplit
implementations
is where the challenge of implementing well-performing
GiST indexes lies.
same
Returns true if two index entries are identical, false otherwise. (An “index entry” is a value of the index's storage type, not necessarily the original indexed column's type.)
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_same(storage_type, storage_type, internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_same); Datum my_same(PG_FUNCTION_ARGS) { prefix_range *v1 = PG_GETARG_PREFIX_RANGE_P(0); prefix_range *v2 = PG_GETARG_PREFIX_RANGE_P(1); bool *result = (bool *) PG_GETARG_POINTER(2); *result = my_eq(v1, v2); PG_RETURN_POINTER(result); }
For historical reasons, the same
function doesn't
just return a Boolean result; instead it has to store the flag
at the location indicated by the third argument. The return
value per se is ignored, though it's conventional to pass back the
address of that argument.
distance
Given an index entry p
and a query value q
,
this function determines the index entry's
“distance” from the query value. This function must be
supplied if the operator class contains any ordering operators.
A query using the ordering operator will be implemented by returning
index entries with the smallest “distance” values first,
so the results must be consistent with the operator's semantics.
For a leaf index entry the result just represents the distance to
the index entry; for an internal tree node, the result must be the
smallest distance that any child entry could have.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_distance(internal, data_type, smallint, oid, internal) RETURNS float8 AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
And the matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_distance); Datum my_distance(PG_FUNCTION_ARGS) { GISTENTRY *entry = (GISTENTRY *) PG_GETARG_POINTER(0); data_type *query = PG_GETARG_DATA_TYPE_P(1); StrategyNumber strategy = (StrategyNumber) PG_GETARG_UINT16(2); /* Oid subtype = PG_GETARG_OID(3); */ /* bool *recheck = (bool *) PG_GETARG_POINTER(4); */ data_type *key = DatumGetDataType(entry->key); double retval; /* * determine return value as a function of strategy, key and query. */ PG_RETURN_FLOAT8(retval); }
The arguments to the distance
function are identical to
the arguments of the consistent
function.
Some approximation is allowed when determining the distance, so long
as the result is never greater than the entry's actual distance. Thus,
for example, distance to a bounding box is usually sufficient in
geometric applications. For an internal tree node, the distance
returned must not be greater than the distance to any of the child
nodes. If the returned distance is not exact, the function must set
*recheck
to true. (This is not necessary for internal tree
nodes; for them, the calculation is always assumed to be inexact.) In
this case the executor will calculate the accurate distance after
fetching the tuple from the heap, and reorder the tuples if necessary.
If the distance function returns *recheck = true
for any
leaf node, the original ordering operator's return type must
be float8
or float4
, and the distance function's
result values must be comparable to those of the original ordering
operator, since the executor will sort using both distance function
results and recalculated ordering-operator results. Otherwise, the
distance function's result values can be any finite float8
values, so long as the relative order of the result values matches the
order returned by the ordering operator. (Infinity and minus infinity
are used internally to handle cases such as nulls, so it is not
recommended that distance
functions return these values.)
fetch
Converts the compressed index representation of a data item into the original data type, for index-only scans. The returned data must be an exact, non-lossy copy of the originally indexed value.
The SQL declaration of the function must look like this:
CREATE OR REPLACE FUNCTION my_fetch(internal) RETURNS internal AS 'MODULE_PATHNAME' LANGUAGE C STRICT;
The argument is a pointer to a GISTENTRY
struct. On
entry, its key
field contains a non-NULL leaf datum in
compressed form. The return value is another GISTENTRY
struct, whose key
field contains the same datum in its
original, uncompressed form. If the opclass's compress function does
nothing for leaf entries, the fetch
method can return the
argument as-is. Or, if the opclass does not have a compress function,
the fetch
method can be omitted as well, since it would
necessarily be a no-op.
The matching code in the C module could then follow this skeleton:
PG_FUNCTION_INFO_V1(my_fetch); Datum my_fetch(PG_FUNCTION_ARGS) { GISTENTRY *entry = (GISTENTRY *) PG_GETARG_POINTER(0); input_data_type *in = DatumGetP(entry->key); fetched_data_type *fetched_data; GISTENTRY *retval; retval = palloc(sizeof(GISTENTRY)); fetched_data = palloc(sizeof(fetched_data_type)); /* * Convert 'fetched_data' into the a Datum of the original datatype. */ /* fill *retval from fetch_data. */ gistentryinit(*retval, PointerGetDatum(converted_datum), entry->rel, entry->page, entry->offset, FALSE); PG_RETURN_POINTER(retval); }
If the compress method is lossy for leaf entries, the operator class
cannot support index-only scans, and must not define
a fetch
function.
All the GiST support methods are normally called in short-lived memory
contexts; that is, CurrentMemoryContext
will get reset after
each tuple is processed. It is therefore not very important to worry about
pfree'ing everything you palloc. However, in some cases it's useful for a
support method to cache data across repeated calls. To do that, allocate
the longer-lived data in fcinfo->flinfo->fn_mcxt
, and
keep a pointer to it in fcinfo->flinfo->fn_extra
. Such
data will survive for the life of the index operation (e.g., a single GiST
index scan, index build, or index tuple insertion). Be careful to pfree
the previous value when replacing a fn_extra
value, or the leak
will accumulate for the duration of the operation.