sqlite> EXPLAIN QUERY PLAN SELECT a, b FROM t1 WHERE a=1;
QUERY PLAN
`--SCAN t1
The example above shows
SQLite picking full-table scan will visit all rows in the table.
If the query were able to use an index, then the
SCAN/SEARCH record would include the name of the index and, for a
SEARCH record, an indication of how the subset of rows visited is
identified. For example:
sqlite> CREATE INDEX i1 ON t1(a);
sqlite> EXPLAIN QUERY PLAN SELECT a, b FROM t1 WHERE a=1;
QUERY PLAN
`--SEARCH t1 USING INDEX i1 (a=?)
The previous example, SQLite uses index "i1" to optimize
a WHERE clause term of the form (a=?) - in this case "a=1".
The previous example could not use a covering index, but the following
example can, and that fact is reflected in the output:
sqlite> CREATE INDEX i2 ON t1(a, b);
sqlite> EXPLAIN QUERY PLAN SELECT a, b FROM t1 WHERE a=1;
QUERY PLAN
`--SEARCH t1 USING COVERING INDEX i2 (a=?)
All joins in SQLite are implemented using nested scans. When a
SELECT query that features a join is analyzed using EXPLAIN QUERY PLAN, one
SCAN or SEARCH record is output for each nested loop. For example:
sqlite> EXPLAIN QUERY PLAN SELECT t1.*, t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2;
QUERY PLAN
|--SEARCH t1 USING INDEX i2 (a=? AND b>?)
`--SCAN t2
The order of the entries indicates the nesting order. In
this case, the scan of table t1 using index i2 is the outer loop (since it
appears first)
and the full-table scan of table t2 is the inner loop (since it appears
last).
In the following example, the positions of t1 and t2 in the FROM
clause of the SELECT are reversed. The query strategy remains the same.
The output from EXPLAIN QUERY PLAN shows how the query is actually
evaluated, not how it is specified in the SQL statement.
sqlite> EXPLAIN QUERY PLAN SELECT t1.*, t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2;
QUERY PLAN
|--SEARCH t1 USING INDEX i2 (a=? AND b>?)
`--SCAN t2
If the WHERE clause of a query contains an OR expression, then SQLite might
use the "OR by union" strategy (also known as the
OR optimization). In this case there will be single top-level record
for the search, with two sub-records, one for each index:
sqlite> CREATE INDEX i3 ON t1(b);
sqlite> EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE a=1 OR b=2;
QUERY PLAN
`--MULTI-INDEX OR
|--SEARCH t1 USING COVERING INDEX i2 (a=?)
`--SEARCH t1 USING INDEX i3 (b=?)
1.2. Temporary Sorting B-Trees
If a SELECT query contains an ORDER BY, GROUP BY or DISTINCT clause,
SQLite may need to use a temporary b-tree structure to sort the output
rows. Or, it might use an index. Using an index is
almost always much more efficient than performing a sort.
If a temporary b-tree is required, a record is added to the EXPLAIN
QUERY PLAN output with the "detail" field set to a string value of
the form "USE TEMP B-TREE FOR xxx", where xxx is one of "ORDER BY",
"GROUP BY" or "DISTINCT". For example:
sqlite> EXPLAIN QUERY PLAN SELECT c, d FROM t2 ORDER BY c;
QUERY PLAN
|--SCAN t2
`--USE TEMP B-TREE FOR ORDER BY
In this case using the temporary b-tree can be avoided by creating an index
on t2(c), as follows:
sqlite> CREATE INDEX i4 ON t2(c);
sqlite> EXPLAIN QUERY PLAN SELECT c, d FROM t2 ORDER BY c;
QUERY PLAN
`--SCAN t2 USING INDEX i4
1.3. Subqueries
In all the examples above, there has only been a single SELECT statement.
If a query contains sub-selects, those are shown as being children of
the outer SELECT. For example:
sqlite> EXPLAIN QUERY PLAN SELECT (SELECT b FROM t1 WHERE a=0), (SELECT a FROM t1 WHERE b=t2.c) FROM t2;
|--SCAN TABLE t2 USING COVERING INDEX i4
|--SCALAR SUBQUERY
| `--SEARCH t1 USING COVERING INDEX i2 (a=?)
`--CORRELATED SCALAR SUBQUERY
`--SEARCH t1 USING INDEX i3 (b=?)
The example above contains two "SCALAR" subqueries. The subqueries
are SCALAR in the sense that they return a single value - a one-row,
one-column table. If the actual query returns more than that, then
only the first column of the first row is used.
The first subquery above is constant with respect to the outer query.
The value for the first subquery can be computed once and then reused
for each row of the outer SELECT. The second subquery, however, is
"CORRELATED". The value of the second subquery changes depending
on values in the current row of the outer query. Hence, the second
subquery must be run once for each output row in the outer SELECT.
Unless the flattening optimization is applied, if a subquery appears in
the FROM clause of a SELECT statement, SQLite can either run the subquery and
stores the results in a temporary table, or it can run the subquery as a
co-routine. The following query is an example of the latter. The subquery
is run by a co-routine. The outer query blocks whenever it needs another
row of input from the subquery. Control switches to the co-routine which
produces the desired output row, then control switches back to the main
routine which continues processing.
sqlite> EXPLAIN QUERY PLAN SELECT count(*)
> FROM (SELECT max(b) AS x FROM t1 GROUP BY a) AS qqq
> GROUP BY x;
QUERY PLAN
|--CO-ROUTINE qqq
| `--SCAN t1 USING COVERING INDEX i2
|--SCAN qqqq
`--USE TEMP B-TREE FOR GROUP BY
If the flattening optimization is used on a subquery in the FROM clause
of a SELECT statement, that effectively merges the subquery into the outer
query. The output of EXPLAIN QUERY PLAN reflects this, as in the following
example:
sqlite> EXPLAIN QUERY PLAN SELECT * FROM (SELECT * FROM t2 WHERE c=1) AS t3, t1;
QUERY PLAN
|--SEARCH t2 USING INDEX i4 (c=?)
`--SCAN t1
If the content of a subquery might need to be visited more than once, then
the use of a co-routine is undesirable, as the co-routine would then have to
compute the data more than once. And if the subquery cannot be flattened,
that means the subquery must be manifested into a transient table.
sqlite> SELECT * FROM
> (SELECT * FROM t1 WHERE a=1 ORDER BY b LIMIT 2) AS x,
> (SELECT * FROM t2 WHERE c=1 ORDER BY d LIMIT 2) AS y;
QUERY PLAN
|--MATERIALIZE x
| `--SEARCH t1 USING COVERING INDEX i2 (a=?)
|--MATERIALIZE y
| |--SEARCH t2 USING INDEX i4 (c=?)
| `--USE TEMP B-TREE FOR ORDER BY
|--SCAN x
`--SCAN y
1.4. Compound Queries
Each component query of a compound query (UNION, UNION ALL, EXCEPT or
INTERSECT) is assigned computed separately and is given its own line in
the EXPLAIN QUERY PLAN output.
sqlite> EXPLAIN QUERY PLAN SELECT a FROM t1 UNION SELECT c FROM t2;
QUERY PLAN
`--COMPOUND QUERY
|--LEFT-MOST SUBQUERY
| `--SCAN t1 USING COVERING INDEX i1
`--UNION USING TEMP B-TREE
`--SCAN t2 USING COVERING INDEX i4
The "USING TEMP B-TREE" clause in the above output indicates that a
temporary b-tree structure is used to implement the UNION of the results
of the two sub-selects. An alternative method of computing a compound
is to run each subquery as a co-routine, arrange for their outputs to
appear in sorted order, and merge the results together. When the query
planner chooses this latter approach, the EXPLAIN QUERY PLAN output
looks like this:
sqlite> EXPLAIN QUERY PLAN SELECT a FROM t1 EXCEPT SELECT d FROM t2 ORDER BY 1;
QUERY PLAN
`--MERGE (EXCEPT)
|--LEFT
