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59.3. Extensibility
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59.3. Extensibility

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. TheGiST 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,Postgres Pro supports extensible B-trees and hash indexes. That means that you can usePostgres Pro 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 aPostgres Pro 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 seven methods that an index operator class for GiST must provide, and two that are optional. Correctness of the index is ensured by proper implementation of thesame,consistent andunion methods, while efficiency (size and speed) of the index will depend on thepenalty andpicksplit methods. The remaining two basic methods arecompress anddecompress, 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 followPostgres Pro data type rules here, see aboutvarlena for variable sized data). If the tree's internal data type exists at the SQL level, theSTORAGE option of theCREATE OPERATOR CLASS command can be used. The optional eighth method isdistance, which is needed if the operator class wishes to support ordered scans (nearest-neighbor searches). The optional ninth methodfetch is needed if the operator class wishes to support index-only scans.

consistent

Given an index entryp and a query valueq, this function determines whether the index entry is“consistent” with the query; that is, could the predicate“indexed_columnindexable_operatorq” 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 istrue, arecheck flag must also be returned. This indicates whether the predicate is certainly true or only possibly true. Ifrecheck =false then the index has tested the predicate condition exactly, whereas ifrecheck =true the row is only a candidate match. In that case the system will automatically evaluate theindexable_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 boolAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_consistent);Datummy_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 andquery the value being looked up in the index. TheStrategyNumber parameter indicates which operator of your operator class is being applied — it matches one of the operator numbers in theCREATE OPERATOR CLASS command. Depending on what operators you have included in the class, the data type ofquery could vary with the operator, but the above skeleton assumes it doesn't.

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 internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_union);Datummy_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 whereunion(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.

Theunion implementation function should return a pointer to newlypalloc()ed memory. You can't just return whatever the input is.

compress

Converts the data item into a format suitable for physical storage in an index page.

The SQL declaration of the function must look like this:

CREATE OR REPLACE FUNCTION my_compress(internal)RETURNS internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_compress);Datummy_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 adaptcompressed_data_type to the specific type you're converting to in order to compress your leaf nodes, of course.

decompress

The reverse of thecompress method. Converts the index representation of the data item into a format that can be manipulated by the other GiST methods in the operator class.

The SQL declaration of the function must look like this:

CREATE OR REPLACE FUNCTION my_decompress(internal)RETURNS internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_decompress);Datummy_decompress(PG_FUNCTION_ARGS){    PG_RETURN_POINTER(PG_GETARG_POINTER(0));}

The above skeleton is suitable for the case where no decompression is needed.

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 leastpenalty in the tree. Values returned bypenalty 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 internalAS '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);Datummy_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);}

Thepenalty 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 internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_picksplit);Datummy_picksplit(PG_FUNCTION_ARGS){    GistEntryVector *entryvec = (GistEntryVector *) PG_GETARG_POINTER(0);    OffsetNumber maxoff = entryvec->n - 1;    GISTENTRY  *ent = entryvec->vector;    GIST_SPLITVEC *v = (GIST_SPLITVEC *) PG_GETARG_POINTER(1);    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);}

Likepenalty, thepicksplit function is crucial to good performance of the index. Designing suitablepenalty andpicksplit implementations is where the challenge of implementing well-performing GiST indexes lies.

same

Returns true if two index entries are identical, false otherwise.

The SQL declaration of the function must look like this:

CREATE OR REPLACE FUNCTION my_same(internal, internal, internal)RETURNS internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_same);Datummy_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, thesame function doesn't just return a Boolean result; instead it has to store the flag at the location indicated by the third argument.

distance

Given an index entryp and a query valueq, 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)RETURNS float8AS 'MODULE_PATHNAME'LANGUAGE C STRICT;

And the matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_distance);Datummy_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 thedistance function are identical to the arguments of theconsistent 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 befloat8 orfloat4, 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 finitefloat8 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 thatdistance functions return these values.)

fetch

Converts the compressed index representation of the 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 internalAS 'MODULE_PATHNAME'LANGUAGE C STRICT;

The argument is a pointer to aGISTENTRY struct. On entry, its 'key' field contains a non-NULL leaf datum in its compressed form. The return value is anotherGISTENTRY struct, whose 'key' field contains the same datum in the original, uncompressed form. If the opclass' compress function does nothing for leaf entries, the fetch method can return the argument as is.

The matching code in the C module could then follow this skeleton:

PG_FUNCTION_INFO_V1(my_fetch);Datummy_fetch(PG_FUNCTION_ARGS){    GISTENTRY  *entry = (GISTENTRY *) PG_GETARG_POINTER(0);    input_data_type *in = DatumGetPointer(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 fetched_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 infcinfo->flinfo->fn_mcxt, and keep a pointer to it infcinfo->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 afn_extra value, or the leak will accumulate for the duration of the operation.

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