11.9. Index-Only Scans and Covering Indexes
All indexes in Postgres Pro are secondary indexes, meaning that each index is stored separately from the table's main data area (which is called the table's heap in Postgres Pro terminology). This means that in an ordinary index scan, each row retrieval requires fetching data from both the index and the heap. Furthermore, while the index entries that match a given indexable
WHERE condition are usually close together in the index, the table rows they reference might be anywhere in the heap. The heap-access portion of an index scan thus involves a lot of random access into the heap, which can be slow, particularly on traditional rotating media. (As described in Section 11.5, bitmap scans try to alleviate this cost by doing the heap accesses in sorted order, but that only goes so far.)
To solve this performance problem, Postgres Pro supports index-only scans, which can answer queries from an index alone without any heap access. The basic idea is to return values directly out of each index entry instead of consulting the associated heap entry. There are two fundamental restrictions on when this method can be used:
The index type must support index-only scans. B-tree indexes always do. GiST and SP-GiST indexes support index-only scans for some operator classes but not others. Other index types have no support. The underlying requirement is that the index must physically store, or else be able to reconstruct, the original data value for each index entry. As a counterexample, GIN indexes cannot support index-only scans because each index entry typically holds only part of the original data value.
The query must reference only columns stored in the index. For example, given an index on columns
yof a table that also has a column
z, these queries could use index-only scans:
SELECT x, y FROM tab WHERE x = 'key'; SELECT x FROM tab WHERE x = 'key' AND y < 42;
but these queries could not:
SELECT x, z FROM tab WHERE x = 'key'; SELECT x FROM tab WHERE x = 'key' AND z < 42;
(Expression indexes and partial indexes complicate this rule, as discussed below.)
If these two fundamental requirements are met, then all the data values required by the query are available from the index, so an index-only scan is physically possible. But there is an additional requirement for any table scan in Postgres Pro: it must verify that each retrieved row be “visible” to the query's MVCC snapshot, as discussed in Chapter 13. Visibility information is not stored in index entries, only in heap entries; so at first glance it would seem that every row retrieval would require a heap access anyway. And this is indeed the case, if the table row has been modified recently. However, for seldom-changing data there is a way around this problem. Postgres Pro tracks, for each page in a table's heap, whether all rows stored in that page are old enough to be visible to all current and future transactions. This information is stored in a bit in the table's visibility map. An index-only scan, after finding a candidate index entry, checks the visibility map bit for the corresponding heap page. If it's set, the row is known visible and so the data can be returned with no further work. If it's not set, the heap entry must be visited to find out whether it's visible, so no performance advantage is gained over a standard index scan. Even in the successful case, this approach trades visibility map accesses for heap accesses; but since the visibility map is four orders of magnitude smaller than the heap it describes, far less physical I/O is needed to access it. In most situations the visibility map remains cached in memory all the time.
In short, while an index-only scan is possible given the two fundamental requirements, it will be a win only if a significant fraction of the table's heap pages have their all-visible map bits set. But tables in which a large fraction of the rows are unchanging are common enough to make this type of scan very useful in practice.
To make effective use of the index-only scan feature, you might choose to create a covering index, which is an index specifically designed to include the columns needed by a particular type of query that you run frequently. Since queries typically need to retrieve more columns than just the ones they search on, Postgres Pro allows you to create an index in which some columns are just “payload” and are not part of the search key. This is done by adding an
INCLUDE clause listing the extra columns. For example, if you commonly run queries like
SELECT y FROM tab WHERE x = 'key';
the traditional approach to speeding up such queries would be to create an index on
x only. However, an index defined as
CREATE INDEX tab_x_y ON tab(x) INCLUDE (y);
could handle these queries as index-only scans, because
y can be obtained from the index without visiting the heap.
y is not part of the index's search key, it does not have to be of a data type that the index can handle; it's merely stored in the index and is not interpreted by the index machinery. Also, if the index is a unique index, that is
CREATE UNIQUE INDEX tab_x_y ON tab(x) INCLUDE (y);
the uniqueness condition applies to just column
x, not to the combination of
INCLUDE clause can also be written in
PRIMARY KEY constraints, providing alternative syntax for setting up an index like this.)
It's wise to be conservative about adding non-key payload columns to an index, especially wide columns. If an index tuple exceeds the maximum size allowed for the index type, data insertion will fail. In any case, non-key columns duplicate data from the index's table and bloat the size of the index, thus potentially slowing searches. And remember that there is little point in including payload columns in an index unless the table changes slowly enough that an index-only scan is likely to not need to access the heap. If the heap tuple must be visited anyway, it costs nothing more to get the column's value from there. Other restrictions are that expressions are not currently supported as included columns, and that only B-tree and GiST indexes currently support included columns.
Before Postgres Pro had the
INCLUDE feature, people sometimes made covering indexes by writing the payload columns as ordinary index columns, that is writing
CREATE INDEX tab_x_y ON tab(x, y);
even though they had no intention of ever using
y as part of a
WHERE clause. This works fine as long as the extra columns are trailing columns; making them be leading columns is unwise for the reasons explained in Section 11.3. However, this method doesn't support the case where you want the index to enforce uniqueness on the key column(s).
Suffix truncation always removes non-key columns from upper B-Tree levels. As payload columns, they are never used to guide index scans. The truncation process also removes one or more trailing key column(s) when the remaining prefix of key column(s) happens to be sufficient to describe tuples on the lowest B-Tree level. In practice, covering indexes without an
INCLUDE clause often avoid storing columns that are effectively payload in the upper levels. However, explicitly defining payload columns as non-key columns reliably keeps the tuples in upper levels small.
In principle, index-only scans can be used with expression indexes. For example, given an index on
x is a table column, it should be possible to execute
SELECT f(x) FROM tab WHERE f(x) < 1;
as an index-only scan; and this is very attractive if
f() is an expensive-to-compute function. However, Postgres Pro's planner is currently not very smart about such cases. It considers a query to be potentially executable by index-only scan only when all columns needed by the query are available from the index. In this example,
x is not needed except in the context
f(x), but the planner does not notice that and concludes that an index-only scan is not possible. If an index-only scan seems sufficiently worthwhile, this can be worked around by adding
x as an included column, for example
CREATE INDEX tab_f_x ON tab (f(x)) INCLUDE (x);
An additional caveat, if the goal is to avoid recalculating
f(x), is that the planner won't necessarily match uses of
f(x) that aren't in indexable
WHERE clauses to the index column. It will usually get this right in simple queries such as shown above, but not in queries that involve joins. These deficiencies may be remedied in future versions of Postgres Pro.
Partial indexes also have interesting interactions with index-only scans. Consider the partial index shown in Example 11.3:
CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target) WHERE success;
In principle, we could do an index-only scan on this index to satisfy a query like
SELECT target FROM tests WHERE subject = 'some-subject' AND success;
But there's a problem: the
WHERE clause refers to
success which is not available as a result column of the index. Nonetheless, an index-only scan is possible because the plan does not need to recheck that part of the
WHERE clause at run time: all entries found in the index necessarily have
success = true so this need not be explicitly checked in the plan. Postgres Pro versions 9.6 and later will recognize such cases and allow index-only scans to be generated, but older versions will not.