SELECT, TABLE, WITH — retrieve rows from a table or view
[ WITH [ RECURSIVE ]with_query
[, ...] ] SELECT [ ALL | UNIQUE | DISTINCT [ ON (expression
[, ...] ) ] ] [ * |expression
[ [ AS ]output_name
] [, ...] ] [ FROMfrom_item
[, ...] ] [ { USE | IGNORE | FORCE } { INDEX | KEY } [ FOR { JOIN | ORDER BY | GROUP BY } ] (index_list) ] [ WHEREcondition
] [ START WITHstart_expression
] [ CONNECT BY { PRIORparent_expr
=child_expr
|child_expr
= PRIORparent_expr
} ] [ GROUP BYgrouping_element
[, ...] [WITH ROLLUP] ] [ HAVINGcondition
] [ WINDOWwindow_name
AS (window_definition
) [, ...] ] [ { UNION | INTERSECT | EXCEPT | MINUS } [ ALL | DISTINCT ]select
] [ ORDER BYexpression
[ ASC | DESC | USINGoperator
] [ NULLS { FIRST | LAST } ] [, ...] ] [ LIMIT {count
| ALL } ] [ OFFSETstart
[ ROW | ROWS ] ] [ FETCH { FIRST | NEXT } [count
] { ROW | ROWS } { ONLY | WITH TIES } ] [ FOR { UPDATE | NO KEY UPDATE | SHARE | KEY SHARE } [ OFtable_name
[, ...] ] [ NOWAIT | SKIP LOCKED ] [...] ] wherefrom_item
can be one of: [ ONLY ]table_name
[ SAMPLE ( argument ) ] [ * ] [ [ AS ]alias
[ (column_alias
[, ...] ) ] ] [ TABLESAMPLEsampling_method
(argument
[, ...] ) [ REPEATABLE (seed
) ] ] [ LATERAL ] (select
) [ AS ]alias
[ (column_alias
[, ...] ) ]with_query_name
[ [ AS ]alias
[ (column_alias
[, ...] ) ] ] [ LATERAL ]function_name
( [argument
[, ...] ] ) [ WITH ORDINALITY ] [ [ AS ]alias
[ (column_alias
[, ...] ) ] ] [ LATERAL ]function_name
( [argument
[, ...] ] ) [ AS ]alias
(column_definition
[, ...] ) [ LATERAL ]function_name
( [argument
[, ...] ] ) AS (column_definition
[, ...] ) [ LATERAL ] ROWS FROM(function_name
( [argument
[, ...] ] ) [ AS (column_definition
[, ...] ) ] [, ...] ) [ WITH ORDINALITY ] [ [ AS ]alias
[ (column_alias
[, ...] ) ] ] [ ONLY ]table_name
[ * ] [ [ AS ]alias
[ (column_alias
[, ...] ) ] ]opt_conversion_clause
(select
) [ AS ]alias
[ (column_alias
[, ...] ) ]opt_conversion_clause
from_item
join_type
from_item
{ ONjoin_condition
| USING (join_column
[, ...] ) }from_item
NATURALjoin_type
from_item
from_item
CROSS JOINfrom_item
andgrouping_element
can be one of: ( )expression
(expression
[, ...] ) ROLLUP ( {expression
| (expression
[, ...] ) } [, ...] ) CUBE ( {expression
| (expression
[, ...] ) } [, ...] ) GROUPING SETS (grouping_element
[, ...] ) andwith_query
is:with_query_name
[ (column_name
[, ...] ) ] AS [ [ NOT ] MATERIALIZED ] (select
|values
|insert
|update
|delete
) TABLE [ ONLY ]table_name
[ * ] andopt_conversion_clause
is:pivot_clause
[ * ] [ AS ]alias
andpivot_clause
is: PIVOT (function_name
(argument
) [ AS ]alias
FORcolumnref
IN (column_definition
[, ...] ) ) [ AS ]alias
SELECT
retrieves rows from zero or more tables.
The general processing of SELECT
is as follows:
All queries in the WITH
list are computed.
These effectively serve as temporary tables that can be referenced
in the FROM
list. A WITH
query
that is referenced more than once in FROM
is
computed only once,
unless specified otherwise with NOT MATERIALIZED
.
(See WITH Clause below.)
All elements in the FROM
list are computed.
(Each element in the FROM
list is a real or
virtual table.) If more than one element is specified in the
FROM
list, they are cross-joined together.
(See FROM Clause below.)
All elements in the USE/FORCE/IGNORE
list are just syntax compatible.
Future version will implementation these feature.
If the WHERE
clause is specified, all rows
that do not satisfy the condition are eliminated from the
output. (See WHERE Clause below.)
You can use '(+)' in condition to specify outer join like oracle. (See oracle plus below.)
If the CONNECT BY
clause is specified, then you can select rows in a hierarchical order. (See CONNECT BY Clause below.)
For each row returned by a hierarchical query, the LEVEL
pseudocolumn returns 1 for a root row, 2 for a child of a root, and so on.
SYS_CONNECT_BY_PATH
is valid only in hierarchical queries. SYS_CONNECT_BY_PATH(column, char) with column
values separated by char
for each row returned by CONNECT BY
condition.
CONNECT_BY_ROOT
is a unary operator that is valid only in hierarchical queries. When you
qualify a column with this operator, returns the column value using data from the root row.
CONNECT BY LEVEL
displays all recursive results below n levels.
<
nCONNECT_BY_ISLEAF
is a pseudocolumn that is frequently used in conjunction with recursive queries using the CONNECT BY clause. It serves the purpose of identifying whether the current row in a hierarchical query is a leaf node (having no child nodes) or not. The CONNECT_BY_ISLEAF
column returns a Boolean value - 1 if the current row is a leaf node (indicating true), and 0 if it is not a leaf node (indicating false).The CONNECT BY rownum
is used to generate sequences.
If the GROUP BY
clause is specified,
or if there are aggregate function calls, the
output is combined into groups of rows that match on one or more
values, and the results of aggregate functions are computed.
If the HAVING
clause is present, it
eliminates groups that do not satisfy the given condition. (See
GROUP BY Clause and
HAVING Clause below.)
The actual output rows are computed using the
SELECT
output expressions for each selected
row or row group. (See SELECT List below.)
SELECT DISTINCT | UNIQUE
eliminates duplicate rows from the
result. SELECT DISTINCT ON
eliminates rows that
match on all the specified expressions. SELECT ALL
(the default) will return all candidate rows, including
duplicates. (See DISTINCT Clause below.)
Using the operators UNION
,
INTERSECT
, and EXCEPT
, the
output of more than one SELECT
statement can
be combined to form a single result set. The
UNION
operator returns all rows that are in
one or both of the result sets. The
INTERSECT
operator returns all rows that are
strictly in both result sets. The EXCEPT
(MINUS
is completely equivalent to EXCEPT
,
so won't repeat it later)
operator returns the rows that are in the first result set but
not in the second. In all three cases, duplicate rows are
eliminated unless ALL
is specified. The noise
word DISTINCT
can be added to explicitly specify
eliminating duplicate rows. Notice that DISTINCT
is
the default behavior here, even though ALL
is
the default for SELECT
itself. (See
UNION Clause, INTERSECT Clause, and
EXCEPT Clause below.)
If the ORDER BY
clause is specified, the
returned rows are sorted in the specified order. If
ORDER BY
is not given, the rows are returned
in whatever order the system finds fastest to produce. (See
ORDER BY Clause below.)
If the LIMIT
(or FETCH FIRST
) or OFFSET
clause is specified, the SELECT
statement
only returns a subset of the result rows. (See LIMIT Clause below.)
If FOR UPDATE
, FOR NO KEY UPDATE
, FOR SHARE
or FOR KEY SHARE
is specified, the
SELECT
statement locks the selected rows
against concurrent updates. (See The Locking Clause
below.)
The START WITH
clause and CONNECT BY
clause as a
whole can be put after GROUP BY
clause.
You must have SELECT
privilege on each column used
in a SELECT
command. The use of FOR NO KEY UPDATE
,
FOR UPDATE
,
FOR SHARE
or FOR KEY SHARE
requires
UPDATE
privilege as well (for at least one column
of each table so selected).
WITH
Clause
The WITH
clause allows you to specify one or more
subqueries that can be referenced by name in the primary query.
The subqueries effectively act as temporary tables or views
for the duration of the primary query.
Each subquery can be a SELECT
, TABLE
, VALUES
,
INSERT
, UPDATE
or
DELETE
statement.
When writing a data-modifying statement (INSERT
,
UPDATE
or DELETE
) in
WITH
, it is usual to include a RETURNING
clause.
It is the output of RETURNING
, not the underlying
table that the statement modifies, that forms the temporary table that is
read by the primary query. If RETURNING
is omitted, the
statement is still executed, but it produces no output so it cannot be
referenced as a table by the primary query.
A name (without schema qualification) must be specified for each
WITH
query. Optionally, a list of column names
can be specified; if this is omitted,
the column names are inferred from the subquery.
If RECURSIVE
is specified, it allows a
SELECT
subquery to reference itself by name. Such a
subquery must have the form
non_recursive_term
UNION [ ALL | DISTINCT ]recursive_term
where the recursive self-reference must appear on the right-hand
side of the UNION
. Only one recursive self-reference
is permitted per query. Recursive data-modifying statements are not
supported, but you can use the results of a recursive
SELECT
query in
a data-modifying statement. See Section 8.8 for
an example.
Another effect of RECURSIVE
is that
WITH
queries need not be ordered: a query
can reference another one that is later in the list. (However,
circular references, or mutual recursion, are not implemented.)
Without RECURSIVE
, WITH
queries
can only reference sibling WITH
queries
that are earlier in the WITH
list.
When there are multiple queries in the WITH
clause, RECURSIVE
should be written only once,
immediately after WITH
. It applies to all queries
in the WITH
clause, though it has no effect on
queries that do not use recursion or forward references.
The primary query and the WITH
queries are all
(notionally) executed at the same time. This implies that the effects of
a data-modifying statement in WITH
cannot be seen from
other parts of the query, other than by reading its RETURNING
output. If two such data-modifying statements attempt to modify the same
row, the results are unspecified.
A key property of WITH
queries is that they
are normally evaluated only once per execution of the primary query,
even if the primary query refers to them more than once.
In particular, data-modifying statements are guaranteed to be
executed once and only once, regardless of whether the primary query
reads all or any of their output.
However, a WITH
query can be marked
NOT MATERIALIZED
to remove this guarantee. In that
case, the WITH
query can be folded into the primary
query much as though it were a simple sub-SELECT
in
the primary query's FROM
clause. This results in
duplicate computations if the primary query refers to
that WITH
query more than once; but if each such use
requires only a few rows of the WITH
query's total
output, NOT MATERIALIZED
can provide a net savings by
allowing the queries to be optimized jointly.
NOT MATERIALIZED
is ignored if it is attached to
a WITH
query that is recursive or is not
side-effect-free (i.e., is not a plain SELECT
containing no volatile functions).
By default, a side-effect-free WITH
query is folded
into the primary query if it is used exactly once in the primary
query's FROM
clause. This allows joint optimization
of the two query levels in situations where that should be semantically
invisible. However, such folding can be prevented by marking the
WITH
query as MATERIALIZED
.
That might be useful, for example, if the WITH
query
is being used as an optimization fence to prevent the planner from
choosing a bad plan.
LightDB versions before v12 never did
such folding, so queries written for older versions might rely on
WITH
to act as an optimization fence.
See Section 8.8 for additional information.
FROM
Clause
The FROM
clause specifies one or more source
tables for the SELECT
. If multiple sources are
specified, the result is the Cartesian product (cross join) of all
the sources. But usually qualification conditions are added (via
WHERE
) to restrict the returned rows to a small subset of the
Cartesian product.
The FROM
clause can contain the following
elements:
table_name
The name (optionally schema-qualified) of an existing table or view.
If ONLY
is specified before the table name, only that
table is scanned. If ONLY
is not specified, the table
and all its descendant tables (if any) are scanned. Optionally,
*
can be specified after the table name to explicitly
indicate that descendant tables are included.
alias
A substitute name for the FROM
item containing the
alias. An alias is used for brevity or to eliminate ambiguity
for self-joins (where the same table is scanned multiple
times). When an alias is provided, it completely hides the
actual name of the table or function; for example given
FROM foo AS f
, the remainder of the
SELECT
must refer to this FROM
item as f
not foo
. If an alias is
written, a column alias list can also be written to provide
substitute names for one or more columns of the table.
TABLESAMPLE sampling_method
( argument
[, ...] ) [ REPEATABLE ( seed
) ]
A TABLESAMPLE
clause after
a table_name
indicates that the
specified sampling_method
should be used to retrieve a subset of the rows in that table.
This sampling precedes the application of any other filters such
as WHERE
clauses.
The standard LightDB distribution
includes two sampling methods, BERNOULLI
and SYSTEM
, and other sampling methods can be
installed in the database via extensions.
The BERNOULLI
and SYSTEM
sampling methods
each accept a single argument
which is the fraction of the table to sample, expressed as a
percentage between 0 and 100. This argument can be
any real
-valued expression. (Other sampling methods might
accept more or different arguments.) These two methods each return
a randomly-chosen sample of the table that will contain
approximately the specified percentage of the table's rows.
The BERNOULLI
method scans the whole table and
selects or ignores individual rows independently with the specified
probability.
The SYSTEM
method does block-level sampling with
each block having the specified chance of being selected; all rows
in each selected block are returned.
The SYSTEM
method is significantly faster than
the BERNOULLI
method when small sampling
percentages are specified, but it may return a less-random sample of
the table as a result of clustering effects.
The optional REPEATABLE
clause specifies
a seed
number or expression to use
for generating random numbers within the sampling method. The seed
value can be any non-null floating-point value. Two queries that
specify the same seed and argument
values will select the same sample of the table, if the table has
not been changed meanwhile. But different seed values will usually
produce different samples.
If REPEATABLE
is not given then a new random
sample is selected for each query, based upon a system-generated seed.
Note that some add-on sampling methods do not
accept REPEATABLE
, and will always produce new
samples on each use.
SAMPLE ( argument
)
It is a Oracle grammar compatible version of TABLESAMPLE which obviously can only
be used in Oracle compatible mode. The sampling method is fixed to BERNOULLI
.
Unlike TABLESAMPLE
, REPEATABLE
clause is not allowed. That means
that a new random sample is selected for each query, based upon a system-generated seed.
select
A sub-SELECT
can appear in the
FROM
clause. This acts as though its
output were created as a temporary table for the duration of
this single SELECT
command. Note that the
sub-SELECT
must be surrounded by
parentheses, and an alias must be
provided for it. A
VALUES command
can also be used here.
with_query_name
A WITH
query is referenced by writing its name,
just as though the query's name were a table name. (In fact,
the WITH
query hides any real table of the same name
for the purposes of the primary query. If necessary, you can
refer to a real table of the same name by schema-qualifying
the table's name.)
An alias can be provided in the same way as for a table.
function_name
Function calls can appear in the FROM
clause. (This is especially useful for functions that return
result sets, but any function can be used.) This acts as
though the function's output were created as a temporary table for the
duration of this single SELECT
command.
If the function's result type is composite (including the case of a
function with multiple OUT
parameters), each
attribute becomes a separate column in the implicit table.
When the optional WITH ORDINALITY
clause is added
to the function call, an additional column of type bigint
will be appended to the function's result column(s). This column
numbers the rows of the function's result set, starting from 1.
By default, this column is named ordinality
.
An alias can be provided in the same way as for a table. If an alias is written, a column alias list can also be written to provide substitute names for one or more attributes of the function's composite return type, including the ordinality column if present.
Multiple function calls can be combined into a
single FROM
-clause item by surrounding them
with ROWS FROM( ... )
. The output of such an item is the
concatenation of the first row from each function, then the second
row from each function, etc. If some of the functions produce fewer
rows than others, null values are substituted for the missing data, so
that the total number of rows returned is always the same as for the
function that produced the most rows.
If the function has been defined as returning the
record
data type, then an alias or the key word
AS
must be present, followed by a column
definition list in the form (
. The column definition list must match the
actual number and types of columns returned by the function.
column_name
data_type
[, ...
])
When using the ROWS FROM( ... )
syntax, if one of the
functions requires a column definition list, it's preferred to put
the column definition list after the function call inside
ROWS FROM( ... )
. A column definition list can be placed
after the ROWS FROM( ... )
construct only if there's just
a single function and no WITH ORDINALITY
clause.
To use ORDINALITY
together with a column definition
list, you must use the ROWS FROM( ... )
syntax and put the
column definition list inside ROWS FROM( ... )
.
join_type
One of
[ INNER ] JOIN
LEFT [ OUTER ] JOIN
RIGHT [ OUTER ] JOIN
FULL [ OUTER ] JOIN
For the INNER
and OUTER
join types, a
join condition must be specified, namely exactly one of
ON
,
join_condition
USING (
,
or join_column
[, ...])NATURAL
. See below for the meaning.
A JOIN
clause combines two FROM
items, which for convenience we will refer to as “tables”,
though in reality they can be any type of FROM
item.
Use parentheses if necessary to determine the order of nesting.
In the absence of parentheses, JOIN
s nest
left-to-right. In any case JOIN
binds more
tightly than the commas separating FROM
-list items.
All the JOIN
options are just a notational
convenience, since they do nothing you couldn't do with plain
FROM
and WHERE
.
CROSS JOIN
and INNER JOIN
produce a simple Cartesian product, the same result as you get from
listing the two tables at the top level of FROM
,
but restricted by the join condition (if any).
CROSS JOIN
is equivalent to INNER JOIN ON
(TRUE)
, that is, no rows are removed by qualification.
These join types are just a notational convenience, since they
do nothing you couldn't do with plain FROM
and
WHERE
.
LEFT OUTER JOIN
returns all rows in the qualified
Cartesian product (i.e., all combined rows that pass its join
condition), plus one copy of each row in the left-hand table
for which there was no right-hand row that passed the join
condition. This left-hand row is extended to the full width
of the joined table by inserting null values for the
right-hand columns. Note that only the JOIN
clause's own condition is considered while deciding which rows
have matches. Outer conditions are applied afterwards.
Conversely, RIGHT OUTER JOIN
returns all the
joined rows, plus one row for each unmatched right-hand row
(extended with nulls on the left). This is just a notational
convenience, since you could convert it to a LEFT
OUTER JOIN
by switching the left and right tables.
FULL OUTER JOIN
returns all the joined rows, plus
one row for each unmatched left-hand row (extended with nulls
on the right), plus one row for each unmatched right-hand row
(extended with nulls on the left).
ON join_condition
join_condition
is
an expression resulting in a value of type
boolean
(similar to a WHERE
clause) that specifies which rows in a join are considered to
match.
USING ( join_column
[, ...] )
A clause of the form USING ( a, b, ... )
is
shorthand for ON left_table.a = right_table.a AND
left_table.b = right_table.b ...
. Also,
USING
implies that only one of each pair of
equivalent columns will be included in the join output, not
both.
NATURAL
NATURAL
is shorthand for a
USING
list that mentions all columns in the two
tables that have matching names. If there are no common
column names, NATURAL
is equivalent
to ON TRUE
.
CROSS JOIN
CROSS JOIN
is equivalent to INNER JOIN ON
(TRUE)
, that is, no rows are removed by qualification.
They produce a simple Cartesian product, the same result as you get from
listing the two tables at the top level of FROM
,
but restricted by the join condition (if any).
LATERAL
The LATERAL
key word can precede a
sub-SELECT
FROM
item. This allows the
sub-SELECT
to refer to columns of FROM
items that appear before it in the FROM
list. (Without
LATERAL
, each sub-SELECT
is
evaluated independently and so cannot cross-reference any other
FROM
item.)
LATERAL
can also precede a function-call
FROM
item, but in this case it is a noise word, because
the function expression can refer to earlier FROM
items
in any case.
A LATERAL
item can appear at top level in the
FROM
list, or within a JOIN
tree. In the
latter case it can also refer to any items that are on the left-hand
side of a JOIN
that it is on the right-hand side of.
When a FROM
item contains LATERAL
cross-references, evaluation proceeds as follows: for each row of the
FROM
item providing the cross-referenced column(s), or
set of rows of multiple FROM
items providing the
columns, the LATERAL
item is evaluated using that
row or row set's values of the columns. The resulting row(s) are
joined as usual with the rows they were computed from. This is
repeated for each row or set of rows from the column source table(s).
The column source table(s) must be INNER
or
LEFT
joined to the LATERAL
item, else
there would not be a well-defined set of rows from which to compute
each set of rows for the LATERAL
item. Thus,
although a construct such as
is syntactically valid, it is
not actually allowed for X
RIGHT JOIN
LATERAL Y
Y
to reference
X
.
opt_conversion_clause
is
PIVOT
PIVOT
only supports single-clustering functions and single-column multi-group scenarios.
As part of the FROM
clause, it can be used in
JOIN
,NATURAL
,LATERAL
connections,-
Complete the function of row to column.
PIVOT
does not support the following five scenarios:
XML
and ANY
keywords are not supported
Multiple aggregate functions are not supported
PIVOT ( SUM(sale_amount), COUNT(sale_amount) FOR customer_id IN (1, 2, 3, 4) );
Multi-column grouping is not supported
PIVOT ( SUM(sale_amount) FOR (customer_id, prod_category) IN ( (1, ‘furniture’) AS furn1, (2, ‘furniture’) AS furn2, (1, ‘electronics’) AS elec1, (2, ‘electronics’) AS elec2 )
IN
( ) is not supported
select * from test123 PIVOT ( SUM(score) as tc FOR course IN ());
The aggregate function argument used in the PIVOT
clause only supports field types,
not numbers types and '*'
WHERE
Clause
The optional WHERE
clause has the general form
WHERE condition
where condition
is
any expression that evaluates to a result of type
boolean
. Any row that does not satisfy this
condition will be eliminated from the output. A row satisfies the
condition if it returns true when the actual row values are
substituted for any variable references.
CONNECT BY
Clause
The optional CONNECT BY
clause has the general form
CONNECT BY { PRIORparent_expr
=child_expr
|child_expr
= PRIORparent_expr
}.
CONNECT BY
specifies the relationship between parent rows and child rows of the hierarchy.
In a hierarchical query, one expression in condition must be qualified with the PRIOR
operator to refer to the parent row.
START
Clause
The optional START WITH
clause has the general form
[ START WITH start_expression
].
START WITH
specifies the root row(s) of the hierarchy.
GROUP BY
Clause
The optional GROUP BY
clause has the general form
GROUP BY grouping_element
[, ...] [WITH ROLLUP]
GROUP BY
will condense into a single row all
selected rows that share the same values for the grouped
expressions. An expression
used inside a
grouping_element
can be an input column name, or the name or ordinal number of an
output column (SELECT
list item), or an arbitrary
expression formed from input-column values. In case of ambiguity,
a GROUP BY
name will be interpreted as an
input-column name rather than an output column name.
If any of GROUPING SETS
, ROLLUP
or
CUBE
are present as grouping elements, then the
GROUP BY
clause as a whole defines some number of
independent grouping sets
. The effect of this is
equivalent to constructing a UNION ALL
between
subqueries with the individual grouping sets as their
GROUP BY
clauses. For further details on the handling
of grouping sets see Section 8.2.4.
Aggregate functions, if any are used, are computed across all rows
making up each group, producing a separate value for each group.
(If there are aggregate functions but no GROUP BY
clause, the query is treated as having a single group comprising all
the selected rows.)
The set of rows fed to each aggregate function can be further filtered by
attaching a FILTER
clause to the aggregate function
call; see Section 5.2.7 for more information. When
a FILTER
clause is present, only those rows matching it
are included in the input to that aggregate function.
When GROUP BY
is present,
or any aggregate functions are present, it is not valid for
the SELECT
list expressions to refer to
ungrouped columns except within aggregate functions or when the
ungrouped column is functionally dependent on the grouped columns,
since there would otherwise be more than one possible value to
return for an ungrouped column. A functional dependency exists if
the grouped columns (or a subset thereof) are the primary key of
the table containing the ungrouped column.Oracle mode is special,
When GROUP BY
is present, if an ungrouped column
is in a subquery and the expression that is equal to that column in
the subquery is in the grouped column, then the ungrouped column is
allowed to appear in the select list.For example:
select a,d from (select a + 1 as a ,b,c, a + 1 as d from test_agg)s group by d;
Keep in mind that all aggregate functions are evaluated before
evaluating any “scalar” expressions in the HAVING
clause or SELECT
list. This means that, for example,
a CASE
expression cannot be used to skip evaluation of
an aggregate function; see Section 5.2.15.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
and FOR KEY SHARE
cannot be
specified with GROUP BY
.
WITH ROLLUP
takes effect in mysql
mode.
The basic value used by WITH ROLLUP
is to generate additional
rows in the aggregate query to provide summary data.
HAVING
Clause
The optional HAVING
clause has the general form
HAVING condition
where condition
is
the same as specified for the WHERE
clause.
HAVING
eliminates group rows that do not
satisfy the condition. HAVING
is different
from WHERE
: WHERE
filters
individual rows before the application of GROUP
BY
, while HAVING
filters group rows
created by GROUP BY
. Each column referenced in
condition
must
unambiguously reference a grouping column, unless the reference
appears within an aggregate function or the ungrouped column is
functionally dependent on the grouping columns.
The presence of HAVING
turns a query into a grouped
query even if there is no GROUP BY
clause. This is the
same as what happens when the query contains aggregate functions but
no GROUP BY
clause. All the selected rows are considered to
form a single group, and the SELECT
list and
HAVING
clause can only reference table columns from
within aggregate functions. Such a query will emit a single row if the
HAVING
condition is true, zero rows if it is not true.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
and FOR KEY SHARE
cannot be
specified with HAVING
.
WINDOW
Clause
The optional WINDOW
clause has the general form
WINDOWwindow_name
AS (window_definition
) [, ...]
where window_name
is
a name that can be referenced from OVER
clauses or
subsequent window definitions, and
window_definition
is
[existing_window_name
] [ PARTITION BYexpression
[, ...] ] [ ORDER BYexpression
[ ASC | DESC | USINGoperator
] [ NULLS { FIRST | LAST } ] [, ...] ] [frame_clause
]
If an existing_window_name
is specified it must refer to an earlier entry in the WINDOW
list; the new window copies its partitioning clause from that entry,
as well as its ordering clause if any. In this case the new window cannot
specify its own PARTITION BY
clause, and it can specify
ORDER BY
only if the copied window does not have one.
The new window always uses its own frame clause; the copied window
must not specify a frame clause.
The elements of the PARTITION BY
list are interpreted in
much the same fashion as elements of a GROUP BY
clause, except that
they are always simple expressions and never the name or number of an
output column.
Another difference is that these expressions can contain aggregate
function calls, which are not allowed in a regular GROUP BY
clause. They are allowed here because windowing occurs after grouping
and aggregation.
Similarly, the elements of the ORDER BY
list are interpreted
in much the same fashion as elements of a statement-level ORDER BY
clause, except that
the expressions are always taken as simple expressions and never the name
or number of an output column.
The optional frame_clause
defines
the window frame for window functions that depend on the
frame (not all do). The window frame is a set of related rows for
each row of the query (called the current row).
The frame_clause
can be one of
{ RANGE | ROWS | GROUPS }frame_start
[frame_exclusion
] { RANGE | ROWS | GROUPS } BETWEENframe_start
ANDframe_end
[frame_exclusion
]
where frame_start
and frame_end
can be one of
UNBOUNDED PRECEDINGoffset
PRECEDING CURRENT ROWoffset
FOLLOWING UNBOUNDED FOLLOWING
and frame_exclusion
can be one of
EXCLUDE CURRENT ROW EXCLUDE GROUP EXCLUDE TIES EXCLUDE NO OTHERS
If frame_end
is omitted it defaults to CURRENT
ROW
. Restrictions are that
frame_start
cannot be UNBOUNDED FOLLOWING
,
frame_end
cannot be UNBOUNDED PRECEDING
,
and the frame_end
choice cannot appear earlier in the
above list of frame_start
and frame_end
options than
the frame_start
choice does — for example
RANGE BETWEEN CURRENT ROW AND
is not allowed.
offset
PRECEDING
The default framing option is RANGE UNBOUNDED PRECEDING
,
which is the same as RANGE BETWEEN UNBOUNDED PRECEDING AND
CURRENT ROW
; it sets the frame to be all rows from the partition start
up through the current row's last peer (a row
that the window's ORDER BY
clause considers
equivalent to the current row; all rows are peers if there
is no ORDER BY
).
In general, UNBOUNDED PRECEDING
means that the frame
starts with the first row of the partition, and similarly
UNBOUNDED FOLLOWING
means that the frame ends with the last
row of the partition, regardless
of RANGE
, ROWS
or GROUPS
mode.
In ROWS
mode, CURRENT ROW
means
that the frame starts or ends with the current row; but
in RANGE
or GROUPS
mode it means
that the frame starts or ends with the current row's first or last peer
in the ORDER BY
ordering.
The offset
PRECEDING
and
offset
FOLLOWING
options
vary in meaning depending on the frame mode.
In ROWS
mode, the offset
is an integer indicating that the frame starts or ends that many rows
before or after the current row.
In GROUPS
mode, the offset
is an integer indicating that the frame starts or ends that many peer
groups before or after the current row's peer group, where
a peer group is a group of rows that are
equivalent according to the window's ORDER BY
clause.
In RANGE
mode, use of
an offset
option requires that there be
exactly one ORDER BY
column in the window definition.
Then the frame contains those rows whose ordering column value is no
more than offset
less than
(for PRECEDING
) or more than
(for FOLLOWING
) the current row's ordering column
value. In these cases the data type of
the offset
expression depends on the data
type of the ordering column. For numeric ordering columns it is
typically of the same type as the ordering column, but for datetime
ordering columns it is an interval
.
In all these cases, the value of the offset
must be non-null and non-negative. Also, while
the offset
does not have to be a simple
constant, it cannot contain variables, aggregate functions, or window
functions.
The frame_exclusion
option allows rows around
the current row to be excluded from the frame, even if they would be
included according to the frame start and frame end options.
EXCLUDE CURRENT ROW
excludes the current row from the
frame.
EXCLUDE GROUP
excludes the current row and its
ordering peers from the frame.
EXCLUDE TIES
excludes any peers of the current
row from the frame, but not the current row itself.
EXCLUDE NO OTHERS
simply specifies explicitly the
default behavior of not excluding the current row or its peers.
Beware that the ROWS
mode can produce unpredictable
results if the ORDER BY
ordering does not order the rows
uniquely. The RANGE
and GROUPS
modes are designed to ensure that rows that are peers in
the ORDER BY
ordering are treated alike: all rows of
a given peer group will be in the frame or excluded from it.
The purpose of a WINDOW
clause is to specify the
behavior of window functions appearing in the query's
SELECT
list or
ORDER BY
clause.
These functions
can reference the WINDOW
clause entries by name
in their OVER
clauses. A WINDOW
clause
entry does not have to be referenced anywhere, however; if it is not
used in the query it is simply ignored. It is possible to use window
functions without any WINDOW
clause at all, since
a window function call can specify its window definition directly in
its OVER
clause. However, the WINDOW
clause saves typing when the same window definition is needed for more
than one window function.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
and FOR KEY SHARE
cannot be
specified with WINDOW
.
Window functions are described in detail in Section 4.5, Section 5.2.8, and Section 8.2.5.
SELECT
List
The SELECT
list (between the key words
SELECT
and FROM
) specifies expressions
that form the output rows of the SELECT
statement. The expressions can (and usually do) refer to columns
computed in the FROM
clause.
Just as in a table, every output column of a SELECT
has a name. In a simple SELECT
this name is just
used to label the column for display, but when the SELECT
is a sub-query of a larger query, the name is seen by the larger query
as the column name of the virtual table produced by the sub-query.
To specify the name to use for an output column, write
AS
output_name
after the column's expression. (You can omit AS
,
but only if the desired output name does not match any
LightDB keyword (see Appendix C). For protection against possible
future keyword additions, it is recommended that you always either
write AS
or double-quote the output name.)
If you do not specify a column name, a name is chosen automatically
by LightDB. If the column's expression
is a simple column reference then the chosen name is the same as that
column's name. In more complex cases a function or type name may be
used, or the system may fall back on a generated name such as
?column?
.
However, the output of columns's name are converted to lowercase even if we
use AS
to specify their alias name specially unless they
are wrapped with double-quote or anti-quote. But it could keep case invariant in
mysql mode which belongs to the database initted with parameter
lightdb_syntax_compatible_type mysql
accompanied with setting
lightdb_sql_mode to 'uppercase_identifier' in the meanwhile. Especially, the
option 'uppercase_identifier' is suggested to be setted in the lightdb.conf instead
of enabling that on session because of this parameter is unexpected to be modified
once it was setted. Lacking either condition above would disable the feature.
For realized this feature, reaching the same effect as mysql, matching select's
column name to storage's value should ignore the case, e.g. column "fOo" in select
to be equaled to "FoO" which store on disk.
It is similarly but slightly different to mysql mode during oracle mode that the guc parameter 'lightdb_oracle_sql_mode' could be setted on session with value 'show_identifier_uppercase' or ''. If 'show_identifier_uppercase' is setted then the column name on displayed feedbacked by executed a select statement would be uppercase by default. Users only could wrapper that column name with double-quote to keep it invariant. Setting 'lightdb_oracle_sql_mode' to '' could disable this function and recovery the default state.
An output column's name can be used to refer to the column's value in
ORDER BY
and GROUP BY
clauses, but not in the
WHERE
or HAVING
clauses; there you must write
out the expression instead.
Instead of an expression, *
can be written in
the output list as a shorthand for all the columns of the selected
rows. Also, you can write
as a
shorthand for the columns coming from just that table. In these
cases it is not possible to specify new names with table_name
.*AS
;
the output column names will be the same as the table columns' names.
According to the SQL standard, the expressions in the output list should
be computed before applying DISTINCT
, ORDER
BY
, or LIMIT
. This is obviously necessary
when using DISTINCT
, since otherwise it's not clear
what values are being made distinct. However, in many cases it is
convenient if output expressions are computed after ORDER
BY
and LIMIT
; particularly if the output list
contains any volatile or expensive functions. With that behavior, the
order of function evaluations is more intuitive and there will not be
evaluations corresponding to rows that never appear in the output.
LightDB will effectively evaluate output expressions
after sorting and limiting, so long as those expressions are not
referenced in DISTINCT
, ORDER BY
or GROUP BY
. (As a counterexample, SELECT
f(x) FROM tab ORDER BY 1
clearly must evaluate f(x)
before sorting.) Output expressions that contain set-returning functions
are effectively evaluated after sorting and before limiting, so
that LIMIT
will act to cut off the output from a
set-returning function.
LightDB versions before 9.6 did not provide any guarantees about the timing of evaluation of output expressions versus sorting and limiting; it depended on the form of the chosen query plan.
DISTINCT
Clause
If SELECT DISTINCT
is specified, all duplicate rows are
removed from the result set (one row is kept from each group of
duplicates). SELECT DISTINCT
. SELECT UNIQUE
are synonymous and SELECT UNIQUE
can only be used in Oracle mode.
SELECT ALL
specifies the opposite: all rows are
kept; that is the default.
SELECT DISTINCT ON (
keeps only the first row of each set of rows where the given
expressions evaluate to equal. The expression
[, ...] )DISTINCT ON
expressions are interpreted using the same rules as for
ORDER BY
(see above). Note that the “first
row” of each set is unpredictable unless ORDER
BY
is used to ensure that the desired row appears first. For
example:
SELECT DISTINCT ON (location) location, time, report FROM weather_reports ORDER BY location, time DESC;
retrieves the most recent weather report for each location. But
if we had not used ORDER BY
to force descending order
of time values for each location, we'd have gotten a report from
an unpredictable time for each location.
The DISTINCT ON
expression(s) must match the leftmost
ORDER BY
expression(s). The ORDER BY
clause
will normally contain additional expression(s) that determine the
desired precedence of rows within each DISTINCT ON
group.
DISTINCT
supports use with CONNECT BY
. For example:
select distinct test_area1.id, test_area1.name, test_area1.pid from test_area1 join test_area2 on test_area1.id = test_area2.id connect by level < 3 order by test_area1.id; select UNIQUE test_area1.id, test_area1.name, test_area1.pid from test_area1 join test_area2 on test_area1.id = test_area2.id connect by level < 3 order by test_area1.id;
Currently, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
and FOR KEY SHARE
cannot be
specified with DISTINCT
.
UNION
Clause
The UNION
clause has this general form:
select_statement
UNION [ ALL | DISTINCT ]select_statement
select_statement
is
any SELECT
statement without an ORDER
BY
, LIMIT
, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
, or FOR KEY SHARE
clause.
(ORDER BY
and LIMIT
can be attached to a
subexpression if it is enclosed in parentheses. Without
parentheses, these clauses will be taken to apply to the result of
the UNION
, not to its right-hand input
expression.)
The UNION
operator computes the set union of
the rows returned by the involved SELECT
statements. A row is in the set union of two result sets if it
appears in at least one of the result sets. The two
SELECT
statements that represent the direct
operands of the UNION
must produce the same
number of columns, and corresponding columns must be of compatible
data types.
The result of UNION
does not contain any duplicate
rows unless the ALL
option is specified.
ALL
prevents elimination of duplicates. (Therefore,
UNION ALL
is usually significantly quicker than
UNION
; use ALL
when you can.)
DISTINCT
can be written to explicitly specify the
default behavior of eliminating duplicate rows.
Multiple UNION
operators in the same
SELECT
statement are evaluated left to right,
unless otherwise indicated by parentheses.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
, FOR SHARE
and
FOR KEY SHARE
cannot be
specified either for a UNION
result or for any input of a
UNION
.
To be compatible with the use of ORACLE
databases, LightDB UNION
statements
support type conversion between NULL
types and other types. If other types cannot be converted to
NULL
types, an error is reported. This feature is only available in ORACLE
mode.
select null cont from dual union all select null cont from dual union all select 2 cont from dual; select null cont from dual union all select null cont from dual union all select sysdate cont from dual; select 2.1 cont from dual union all select 3.1 cont from dual union all select 4.1 cont from dual union all select 5.1 cont from dual union all select '3.65' cont from dual;
INTERSECT
Clause
The INTERSECT
clause has this general form:
select_statement
INTERSECT [ ALL | DISTINCT ]select_statement
select_statement
is
any SELECT
statement without an ORDER
BY
, LIMIT
, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
, or FOR KEY SHARE
clause.
The INTERSECT
operator computes the set
intersection of the rows returned by the involved
SELECT
statements. A row is in the
intersection of two result sets if it appears in both result sets.
The result of INTERSECT
does not contain any
duplicate rows unless the ALL
option is specified.
With ALL
, a row that has m
duplicates in the
left table and n
duplicates in the right table will appear
min(m
,n
) times in the result set.
DISTINCT
can be written to explicitly specify the
default behavior of eliminating duplicate rows.
Multiple INTERSECT
operators in the same
SELECT
statement are evaluated left to right,
unless parentheses dictate otherwise.
INTERSECT
binds more tightly than
UNION
. That is, A UNION B INTERSECT
C
will be read as A UNION (B INTERSECT
C)
.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
, FOR SHARE
and
FOR KEY SHARE
cannot be
specified either for an INTERSECT
result or for any input of
an INTERSECT
.
EXCEPT
Clause
The EXCEPT
clause has this general form:
select_statement
EXCEPT [ ALL | DISTINCT ]select_statement
select_statement
is
any SELECT
statement without an ORDER
BY
, LIMIT
, FOR NO KEY UPDATE
, FOR UPDATE
,
FOR SHARE
, or FOR KEY SHARE
clause.
The EXCEPT
operator computes the set of rows
that are in the result of the left SELECT
statement but not in the result of the right one.
The result of EXCEPT
does not contain any
duplicate rows unless the ALL
option is specified.
With ALL
, a row that has m
duplicates in the
left table and n
duplicates in the right table will appear
max(m
-n
,0) times in the result set.
DISTINCT
can be written to explicitly specify the
default behavior of eliminating duplicate rows.
Multiple EXCEPT
operators in the same
SELECT
statement are evaluated left to right,
unless parentheses dictate otherwise. EXCEPT
binds at
the same level as UNION
.
Currently, FOR NO KEY UPDATE
, FOR UPDATE
, FOR SHARE
and
FOR KEY SHARE
cannot be
specified either for an EXCEPT
result or for any input of
an EXCEPT
.
ORDER BY
Clause
The optional ORDER BY
clause has this general form:
ORDER BYexpression
[ ASC | DESC | USINGoperator
] [ NULLS { FIRST | LAST } ] [, ...]
The ORDER BY
clause causes the result rows to
be sorted according to the specified expression(s). If two rows are
equal according to the leftmost expression, they are compared
according to the next expression and so on. If they are equal
according to all specified expressions, they are returned in
an implementation-dependent order.
Each expression
can be the
name or ordinal number of an output column
(SELECT
list item), or it can be an arbitrary
expression formed from input-column values, or any expression composed
of aliases of columns in the select list of the same level query
(except stored procedure parameters, window functions, rownum, and volatile functions).
The ordinal number refers to the ordinal (left-to-right) position
of the output column. This feature makes it possible to define an
ordering on the basis of a column that does not have a unique
name. This is never absolutely necessary because it is always
possible to assign a name to an output column using the
AS
clause.
It is also possible to use arbitrary expressions in the
ORDER BY
clause, including columns that do not
appear in the SELECT
output list. Thus the
following statement is valid:
SELECT name FROM distributors ORDER BY code;
A limitation of this feature is that an ORDER BY
clause applying to the result of a UNION
,
INTERSECT
, or EXCEPT
clause can only
specify an output column name or number, not an expression.
If an ORDER BY
expression is a simple name that
matches both an output column name and an input column name,
ORDER BY
will interpret it as the output column name.
This is the opposite of the choice that GROUP BY
will
make in the same situation. This inconsistency is made to be
compatible with the SQL standard.
Optionally one can add the key word ASC
(ascending) or
DESC
(descending) after any expression in the
ORDER BY
clause. If not specified, ASC
is
assumed by default. Alternatively, a specific ordering operator
name can be specified in the USING
clause.
An ordering operator must be a less-than or greater-than
member of some B-tree operator family.
ASC
is usually equivalent to USING <
and
DESC
is usually equivalent to USING >
.
(But the creator of a user-defined data type can define exactly what the
default sort ordering is, and it might correspond to operators with other
names.)
If NULLS LAST
is specified, null values sort after all
non-null values; if NULLS FIRST
is specified, null values
sort before all non-null values. If neither is specified, the default
behavior is NULLS LAST
when ASC
is specified
or implied, and NULLS FIRST
when DESC
is specified
(thus, the default is to act as though nulls are larger than non-nulls).
When USING
is specified, the default nulls ordering depends
on whether the operator is a less-than or greater-than operator.
Note that ordering options apply only to the expression they follow;
for example ORDER BY x, y DESC
does not mean
the same thing as ORDER BY x DESC, y DESC
.
Character-string data is sorted according to the collation that applies
to the column being sorted. That can be overridden at need by including
a COLLATE
clause in the
expression
, for example
ORDER BY mycolumn COLLATE "en_US"
.
For more information see Section 5.2.10 and
Section 22.2.
LIMIT
Clause
The LIMIT
clause consists of two independent
sub-clauses:
LIMIT {count
| ALL } OFFSETstart
The parameter count
specifies the
maximum number of rows to return, while start
specifies the number of rows
to skip before starting to return rows. When both are specified,
start
rows are skipped
before starting to count the count
rows to be returned.
If the count
expression
evaluates to NULL, it is treated as LIMIT ALL
, i.e., no
limit. If start
evaluates
to NULL, it is treated the same as OFFSET 0
.
SQL:2008 introduced a different syntax to achieve the same result, which LightDB also supports. It is:
OFFSETstart
{ ROW | ROWS } FETCH { FIRST | NEXT } [count
] { ROW | ROWS } { ONLY | WITH TIES }
In this syntax, the start
or count
value is required by
the standard to be a literal constant, a parameter, or a variable name;
as a LightDB extension, other expressions
are allowed, but will generally need to be enclosed in parentheses to avoid
ambiguity.
If count
is
omitted in a FETCH
clause, it defaults to 1.
The WITH TIES
option is used to return any additional
rows that tie for the last place in the result set according to
the ORDER BY
clause; ORDER BY
is mandatory in this case, and SKIP LOCKED
is
not allowed.
ROW
and ROWS
as well as
FIRST
and NEXT
are noise
words that don't influence the effects of these clauses.
According to the standard, the OFFSET
clause must come
before the FETCH
clause if both are present; but
LightDB is laxer and allows either order.
When using LIMIT
, it is a good idea to use an
ORDER BY
clause that constrains the result rows into a
unique order. Otherwise you will get an unpredictable subset of
the query's rows — you might be asking for the tenth through
twentieth rows, but tenth through twentieth in what ordering? You
don't know what ordering unless you specify ORDER BY
.
The query planner takes LIMIT
into account when
generating a query plan, so you are very likely to get different
plans (yielding different row orders) depending on what you use
for LIMIT
and OFFSET
. Thus, using
different LIMIT
/OFFSET
values to select
different subsets of a query result will give
inconsistent results unless you enforce a predictable
result ordering with ORDER BY
. This is not a bug; it
is an inherent consequence of the fact that SQL does not promise
to deliver the results of a query in any particular order unless
ORDER BY
is used to constrain the order.
It is even possible for repeated executions of the same LIMIT
query to return different subsets of the rows of a table, if there
is not an ORDER BY
to enforce selection of a deterministic
subset. Again, this is not a bug; determinism of the results is
simply not guaranteed in such a case.
FOR UPDATE
, FOR NO KEY UPDATE
, FOR SHARE
and FOR KEY SHARE
are locking clauses; they affect how SELECT
locks rows as they are obtained from the table.
The locking clause has the general form
FORlock_strength
[ OFtable_name
[, ...] ] [ NOWAIT | SKIP LOCKED ]
where lock_strength
can be one of
UPDATE NO KEY UPDATE SHARE KEY SHARE
For more information on each row-level lock mode, refer to Section 14.3.2.
To prevent the operation from waiting for other transactions to commit,
use either the NOWAIT
or SKIP LOCKED
option. With NOWAIT
, the statement reports an error, rather
than waiting, if a selected row cannot be locked immediately.
With SKIP LOCKED
, any selected rows that cannot be
immediately locked are skipped. Skipping locked rows provides an
inconsistent view of the data, so this is not suitable for general purpose
work, but can be used to avoid lock contention with multiple consumers
accessing a queue-like table.
Note that NOWAIT
and SKIP LOCKED
apply only
to the row-level lock(s) — the required ROW SHARE
table-level lock is still taken in the ordinary way (see
Chapter 14). You can use
LOCK
with the NOWAIT
option first,
if you need to acquire the table-level lock without waiting.
If specific tables are named in a locking clause,
then only rows coming from those tables are locked; any other
tables used in the SELECT
are simply read as
usual. A locking
clause without a table list affects all tables used in the statement.
If a locking clause is
applied to a view or sub-query, it affects all tables used in
the view or sub-query.
However, these clauses
do not apply to WITH
queries referenced by the primary query.
If you want row locking to occur within a WITH
query, specify
a locking clause within the WITH
query.
Multiple locking
clauses can be written if it is necessary to specify different locking
behavior for different tables. If the same table is mentioned (or
implicitly affected) by more than one locking clause,
then it is processed as if it was only specified by the strongest one.
Similarly, a table is processed
as NOWAIT
if that is specified in any of the clauses
affecting it. Otherwise, it is processed
as SKIP LOCKED
if that is specified in any of the
clauses affecting it.
The locking clauses cannot be used in contexts where returned rows cannot be clearly identified with individual table rows; for example they cannot be used with aggregation.
When a locking clause
appears at the top level of a SELECT
query, the rows that
are locked are exactly those that are returned by the query; in the
case of a join query, the rows locked are those that contribute to
returned join rows. In addition, rows that satisfied the query
conditions as of the query snapshot will be locked, although they
will not be returned if they were updated after the snapshot
and no longer satisfy the query conditions. If a
LIMIT
is used, locking stops
once enough rows have been returned to satisfy the limit (but note that
rows skipped over by OFFSET
will get locked). Similarly,
if a locking clause
is used in a cursor's query, only rows actually fetched or stepped past
by the cursor will be locked.
When a locking clause
appears in a sub-SELECT
, the rows locked are those
returned to the outer query by the sub-query. This might involve
fewer rows than inspection of the sub-query alone would suggest,
since conditions from the outer query might be used to optimize
execution of the sub-query. For example,
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss WHERE col1 = 5;
will lock only rows having col1 = 5
, even though that
condition is not textually within the sub-query.
It is possible for a SELECT
command running at the READ
COMMITTED
transaction isolation level and using ORDER
BY
and a locking clause to return rows out of
order. This is because ORDER BY
is applied first.
The command sorts the result, but might then block trying to obtain a lock
on one or more of the rows. Once the SELECT
unblocks, some
of the ordering column values might have been modified, leading to those
rows appearing to be out of order (though they are in order in terms
of the original column values). This can be worked around at need by
placing the FOR UPDATE/SHARE
clause in a sub-query,
for example
SELECT * FROM (SELECT * FROM mytable FOR UPDATE) ss ORDER BY column1;
Note that this will result in locking all rows of mytable
,
whereas FOR UPDATE
at the top level would lock only the
actually returned rows. This can make for a significant performance
difference, particularly if the ORDER BY
is combined with
LIMIT
or other restrictions. So this technique is recommended
only if concurrent updates of the ordering columns are expected and a
strictly sorted result is required.
At the REPEATABLE READ
or SERIALIZABLE
transaction isolation level this would cause a serialization failure (with
a SQLSTATE
of '40001'
), so there is
no possibility of receiving rows out of order under these isolation levels.
TABLE
CommandThe command
TABLE name
is equivalent to
SELECT * FROM name
It can be used as a top-level command or as a space-saving syntax
variant in parts of complex queries. Only the WITH
,
UNION
, INTERSECT
, EXCEPT
,
ORDER BY
, LIMIT
, OFFSET
,
FETCH
and FOR
locking clauses can be used
with TABLE
; the WHERE
clause and any form of
aggregation cannot
be used.
To display the column's names invariant in mysql mode:
CREATE DATABASE films_distributors WITH lightdb_syntax_compatible_type mysql; \c films_distributors; -- it not suggest to set 'uppercase_identifier' on session to enable that as -- 'set lightdb_sql_mode to uppercase_identifier;'. users should specify this -- option in lightdb.conf instead, which follows by the current value of -- 'lightdb_sql_mode' split with ','. Excuting 'lt_ctl --reload' to reload this -- rule and don't modifiy it as far as possible. SELECT Title as tiTLe, Did DiD, name, DAte_pROd, films.KIND FROM films; tiTLe | DiD | name | DAte_pROd | KIND -------------------+-----+--------------+------------+---------- The Third Man | 101 | British Lion | 1949-12-23 | Drama The African Queen | 101 | British Lion | 1951-08-11 | Romantic ...
To display the column's names in uppercase during oracle mode:
-- must ensure in oracle session show lightdb_dblevel_syntax_compatible_type; lightdb_dblevel_syntax_compatible_type ---------------------------------------- Oracle (1 row) set lightdb_oracle_sql_mode to 'show_identifier_uppercase'; show lightdb_oracle_sql_mode; lightdb_oracle_sql_mode --------------------------- show_identifier_uppercase (1 row) create table a(foo varchar(10)); -- foo in inner select not transform to upper case as follow: select "foo" from (select foo as Foo from a) as temp; -- foo in show foo ----- (0 rows) select foo from (select foo as Foo from a) as temp; -- FOO in show FOO ----- (0 rows) select "foO" foo from (select foo as Foo from a) as temp; -- failed, column "foO" does not exist ERROR: column "foO" does not exist LINE 1: select "foO" foo from (select foo as Foo from a) as temp;
To join the table films
with the table
distributors
:
SELECT f.title, f.did, d.name, f.date_prod, f.kind FROM distributors d JOIN films f USING (did); title | did | name | date_prod | kind -------------------+-----+--------------+------------+---------- The Third Man | 101 | British Lion | 1949-12-23 | Drama The African Queen | 101 | British Lion | 1951-08-11 | Romantic ...
To sum the column len
of all films and group
the results by kind
:
SELECT kind, sum(len) AS total FROM films GROUP BY kind; kind | total ----------+------- Action | 07:34 Comedy | 02:58 Drama | 14:28 Musical | 06:42 Romantic | 04:38
To sum the column len
of all films, group
the results by kind
and show those group totals
that are less than 5 hours:
SELECT kind, sum(len) AS total FROM films GROUP BY kind HAVING sum(len) < interval '5 hours'; kind | total ----------+------- Comedy | 02:58 Romantic | 04:38
The following two examples are identical ways of sorting the individual
results according to the contents of the second column
(name
):
SELECT * FROM distributors ORDER BY name; SELECT * FROM distributors ORDER BY 2; did | name -----+------------------ 109 | 20th Century Fox 110 | Bavaria Atelier 101 | British Lion 107 | Columbia 102 | Jean Luc Godard 113 | Luso films 104 | Mosfilm 103 | Paramount 106 | Toho 105 | United Artists 111 | Walt Disney 112 | Warner Bros. 108 | Westward
The next example shows how to obtain the union of the tables
distributors
and
actors
, restricting the results to those that begin
with the letter W in each table. Only distinct rows are wanted, so the
key word ALL
is omitted.
distributors: actors: did | name id | name -----+-------------- ----+---------------- 108 | Westward 1 | Woody Allen 111 | Walt Disney 2 | Warren Beatty 112 | Warner Bros. 3 | Walter Matthau ... ... SELECT distributors.name FROM distributors WHERE distributors.name LIKE 'W%' UNION SELECT actors.name FROM actors WHERE actors.name LIKE 'W%'; name ---------------- Walt Disney Walter Matthau Warner Bros. Warren Beatty Westward Woody Allen
This example shows how to use a function in the FROM
clause, both with and without a column definition list:
CREATE FUNCTION distributors(int) RETURNS SETOF distributors AS $$ SELECT * FROM distributors WHERE did = $1; $$ LANGUAGE SQL; SELECT * FROM distributors(111); did | name -----+------------- 111 | Walt Disney CREATE FUNCTION distributors_2(int) RETURNS SETOF record AS $$ SELECT * FROM distributors WHERE did = $1; $$ LANGUAGE SQL; SELECT * FROM distributors_2(111) AS (f1 int, f2 text); f1 | f2 -----+------------- 111 | Walt Disney
Here is an example of a function with an ordinality column added:
SELECT * FROM unnest(ARRAY['a','b','c','d','e','f']) WITH ORDINALITY; unnest | ordinality --------+---------- a | 1 b | 2 c | 3 d | 4 e | 5 f | 6 (6 rows)
This example shows how to use a simple WITH
clause:
WITH t AS ( SELECT random() as x FROM generate_series(1, 3) ) SELECT * FROM t UNION ALL SELECT * FROM t x -------------------- 0.534150459803641 0.520092216785997 0.0735620250925422 0.534150459803641 0.520092216785997 0.0735620250925422
Notice that the WITH
query was evaluated only once,
so that we got two sets of the same three random values.
This example uses WITH RECURSIVE
to find all
subordinates (direct or indirect) of the employee Mary, and their
level of indirectness, from a table that shows only direct
subordinates:
WITH RECURSIVE employee_recursive(distance, employee_name, manager_name) AS ( SELECT 1, employee_name, manager_name FROM employee WHERE manager_name = 'Mary' UNION ALL SELECT er.distance + 1, e.employee_name, e.manager_name FROM employee_recursive er, employee e WHERE er.employee_name = e.manager_name ) SELECT distance, employee_name FROM employee_recursive;
Notice the typical form of recursive queries:
an initial condition, followed by UNION
,
followed by the recursive part of the query. Be sure that the
recursive part of the query will eventually return no tuples, or
else the query will loop indefinitely. (See Section 8.8
for more examples.)
This example uses LATERAL
to apply a set-returning function
get_product_names()
for each row of the
manufacturers
table:
SELECT m.name AS mname, pname FROM manufacturers m, LATERAL get_product_names(m.id) pname;
Manufacturers not currently having any products would not appear in the result, since it is an inner join. If we wished to include the names of such manufacturers in the result, we could do:
SELECT m.name AS mname, pname FROM manufacturers m LEFT JOIN LATERAL get_product_names(m.id) pname ON true;
This example uses the CONNECT BY
clause to define the relationship between employees and managers, uses the LEVEL
pseudocolumn to show parent and child rows and uses the START WITH
clause to specify a root row for the hierarchy.
SELECT last_name, employee_id, manager_id, LEVEL FROM employees START WITH employee_id = 100 CONNECT BY PRIOR employee_id = manager_id; LAST_NAME EMPLOYEE_ID MANAGER_ID LEVEL ------------------------- ----------- ---------- ---------- King 100 1 Cambrault 148 100 2 Bates 172 148 3 Bloom 169 148 3 Fox 170 148 3 Kumar 173 148 3 Ozer 168 148 3 Smith 171 148 3 De Haan 102 100 2 Hunold 103 102 3 Austin 105 103 4 Ernst 104 103 4 Lorentz 107 103 4 Pataballa 106 103 4 Errazuriz 147 100 2 Ande 166 147 3 Banda 167 147 3
The following example returns the path of employee names from employee KING to all employees of KING (and their employees):
SELECT SYS_CONNECT_BY_PATH(last_name, '/') "Path" FROM employees START WITH last_name = 'KING' CONNECT BY PRIOR employee_id = manager_id; Path ------------------------- /KING /KING/JONES /KING/BLAKE /KING/CLARK /KING/BLAKE/ALLEN /KING/BLAKE/WARD /KING/BLAKE/MARTIN /KING/JONES/SCOTT /KING/BLAKE/TURNER /KING/BLAKE/JAMES /KING/JONES/FORD /KING/CLARK/MILLER /KING/JONES/FORD/SMITH /KING/JONES/SCOTT/ADAMS (14 rows)
The following example returns the last name of each employee in department 110, each manager at the highest level above that employee in the hierarchy, the number of levels between manager and employee, and the path between the two:
SELECT last_name "Employee", CONNECT_BY_ROOT last_name "Manager", LEVEL-1 "Pathlen", SYS_CONNECT_BY_PATH(last_name, '/') "Path" FROM employees WHERE LEVEL > 1 and department_id = 110 CONNECT BY PRIOR employee_id = manager_id ORDER BY "Employee", "Manager", "Pathlen", "Path"; Employee Manager Pathlen Path --------------- --------------- ---------- ------------------------------ Gietz Higgins 1 /Higgins/Gietz Gietz King 3 /King/Kochhar/Higgins/Gietz Gietz Kochhar 2 /Kochhar/Higgins/Gietz Higgins King 2 /King/Kochhar/Higgins Higgins Kochhar 1 /Kochhar/Higgins
The following example display all recursive results below n levels.
select * from staff_table connect by level <
2;
staff_id | name | manager_id
----------+-------------------+------------
1001 | Michael North |
1002 | Megan Berry | 1001
1003 | Sarah Berry | 1001
1004 | Zoe Black | 1001
1005 | Tim James | 1001
1006 | Bella Tucker | 1002
1007 | Ryan Metcalfe | 1002
1008 | Max Mills | 1002
1009 | Benjamin Glover | 1002
1010 | Carolyn Henderson | 1003
1011 | Nicola Kelly | 1003
1012 | Alexandra Climo | 1003
1013 | Dominic King | 1003
1014 | Leonard Gray | 1004
1015 | Eric Rampling | 1004
1016 | Piers Paige | 1007
1017 | Ryan Henderson | 1007
1018 | Frank Tucker | 1008
1019 | Nathan Ferguson | 1008
1020 | Kevin Rampling | 1008
The following example display employees if they are leaf nodes (no subordinates) or not.
SELECT staff_id, name, manager_id, SYS_CONNECT_BY_PATH (name,'/'), connect_by_isleaf FROM staff_table START WITH staff_id = '1001' CONNECT BY PRIOR staff_id = manager_id; staff_id | name | manager_id | sysconnectpath | connect_by_isleaf ----------+-------------------+------------+---------------------------------------------------------+------------------- 1001 | Michael North | 1000 | /Michael North | 0 1002 | Megan Berry | 1001 | /Michael North/Megan Berry | 0 1003 | Sarah Berry | 1001 | /Michael North/Sarah Berry | 0 1004 | Zoe Black | 1001 | /Michael North/Zoe Black | 0 1005 | Tim James | 1001 | /Michael North/Tim James | 1 1006 | Bella Tucker | 1002 | /Michael North/Megan Berry/Bella Tucker | 1 1007 | Ryan Metcalfe | 1002 | /Michael North/Megan Berry/Ryan Metcalfe | 0 1008 | Max Mills | 1002 | /Michael North/Megan Berry/Max Mills | 0 1009 | Benjamin Glover | 1002 | /Michael North/Megan Berry/Benjamin Glover | 1 1010 | Carolyn Henderson | 1003 | /Michael North/Sarah Berry/Carolyn Henderson | 1 1011 | Nicola Kelly | 1003 | /Michael North/Sarah Berry/Nicola Kelly | 1 1012 | Alexandra Climo | 1003 | /Michael North/Sarah Berry/Alexandra Climo | 1 1013 | Dominic King | 1003 | /Michael North/Sarah Berry/Dominic King | 1 1014 | Leonard Gray | 1004 | /Michael North/Zoe Black/Leonard Gray | 1 1015 | Eric Rampling | 1004 | /Michael North/Zoe Black/Eric Rampling | 1 1016 | Piers Paige | 1007 | /Michael North/Megan Berry/Ryan Metcalfe/Piers Paige | 1 1017 | Ryan Henderson | 1007 | /Michael North/Megan Berry/Ryan Metcalfe/Ryan Henderson | 1 1018 | Frank Tucker | 1008 | /Michael North/Megan Berry/Max Mills/Frank Tucker | 1 1019 | Nathan Ferguson | 1008 | /Michael North/Megan Berry/Max Mills/Nathan Ferguson | 1 1020 | Kevin Rampling | 1008 | /Michael North/Megan Berry/Max Mills/Kevin Rampling | 1 (20 rows)
The following example is used to generate sequences for '1 2 3 4 5 6'.
select rownum from dual CONNECT BY rownum <=
6;
rownum
--------
1
2
3
4
5
6
(6 rows)
This example illustrate mysql index hint usage.
-- multiple index select * from lt_test_mysql_ddl use index(pk_lt_test_mysql_ddl,uk_lt_test_mysql_ddl); select * from lt_test_mysql_ddl force index(pk_lt_test_mysql_ddl,uk_lt_test_mysql_ddl); select * from lt_test_mysql_ddl ignore index(pk_lt_test_mysql_ddl,uk_lt_test_mysql_ddl); -- multiple table join select * from lt_test_mysql_ddl a use index for order by(primary) join b using(id); select * from lt_test_mysql_ddl a force index for order by(pk_lt_test_mysql_ddl) join b using(id); select * from lt_test_mysql_ddl a ignore index for order by(primary,pk_lt_test_mysql_ddl) join b using(id); select * from lt_test_mysql_ddl a ignore index for order by(pk_lt_test_mysql_ddl) join b using(id);
Of course, the SELECT
statement is compatible
with the SQL standard. But there are some extensions and some
missing features.
FROM
Clauses
LightDB allows one to omit the
FROM
clause. It has a straightforward use to
compute the results of simple expressions:
SELECT 2+2; ?column? ---------- 4
Some other SQL databases cannot do this except
by introducing a dummy one-row table from which to do the
SELECT
.
Note that if a FROM
clause is not specified,
the query cannot reference any database tables. For example, the
following query is invalid:
SELECT distributors.* WHERE distributors.name = 'Westward';
SELECT
Lists
The list of output expressions after SELECT
can be
empty, producing a zero-column result table.
This is not valid syntax according to the SQL standard.
LightDB allows it to be consistent with
allowing zero-column tables.
However, an empty list is not allowed when DISTINCT
is used.
AS
Key Word
In the SQL standard, the optional key word AS
can be
omitted before an output column name whenever the new column name
is a valid column name (that is, not the same as any reserved
keyword). LightDB is slightly more
restrictive: AS
is required if the new column name
matches any keyword at all, reserved or not. Recommended practice is
to use AS
or double-quote output column names, to prevent
any possible conflict against future keyword additions.
In FROM
items, both the standard and
LightDB allow AS
to
be omitted before an alias that is an unreserved keyword. But
this is impractical for output column names, because of syntactic
ambiguities.
ONLY
and Inheritance
The SQL standard requires parentheses around the table name when
writing ONLY
, for example SELECT * FROM ONLY
(tab1), ONLY (tab2) WHERE ...
. LightDB
considers these parentheses to be optional.
LightDB allows a trailing *
to be written to
explicitly specify the non-ONLY
behavior of including
child tables. The standard does not allow this.
(These points apply equally to all SQL commands supporting the
ONLY
option.)
TABLESAMPLE
Clause Restrictions
The TABLESAMPLE
clause is currently accepted only on
regular tables. According to the SQL standard
it should be possible to apply it to any FROM
item.
The TABLESAMPLE
clause can NOT be used with SAMPLE
clause in one SQL in Oracle compatible mode.
SAMPLE
Clause Restrictions
The SAMPLE
clause can only be used in Oracle
compatible mode, and can NOT be used with TABLESAMPLE
clause
in one SQL.
FROM
LightDB allows a function call to be
written directly as a member of the FROM
list. In the SQL
standard it would be necessary to wrap such a function call in a
sub-SELECT
; that is, the syntax
FROM
is approximately equivalent to
func
(...) alias
FROM LATERAL (SELECT
.
Note that func
(...)) alias
LATERAL
is considered to be implicit; this is
because the standard requires LATERAL
semantics for an
UNNEST()
item in FROM
.
LightDB treats UNNEST()
the
same as other set-returning functions.
GROUP BY
and ORDER BY
In the SQL-92 standard, an ORDER BY
clause can
only use output column names or numbers, while a GROUP
BY
clause can only use expressions based on input column
names. LightDB extends each of
these clauses to allow the other choice as well (but it uses the
standard's interpretation if there is ambiguity).
LightDB also allows both clauses to
specify arbitrary expressions. Note that names appearing in an
expression will always be taken as input-column names, not as
output-column names.
SQL:1999 and later use a slightly different definition which is not
entirely upward compatible with SQL-92.
In most cases, however, LightDB
will interpret an ORDER BY
or GROUP
BY
expression the same way SQL:1999 does.
LightDB recognizes functional dependency
(allowing columns to be omitted from GROUP BY
) only when
a table's primary key is included in the GROUP BY
list.
The SQL standard specifies additional conditions that should be
recognized.
LIMIT
and OFFSET
The clauses LIMIT
and OFFSET
are LightDB-specific syntax, also
used by MySQL. The SQL:2008 standard
has introduced the clauses OFFSET ... FETCH {FIRST|NEXT}
...
for the same functionality, as shown above
in LIMIT Clause. This
syntax is also used by IBM DB2.
(Applications written for Oracle
frequently use a workaround involving the automatically
generated rownum
column, which is not available in
LightDB, to implement the effects of these clauses.)
FOR NO KEY UPDATE
, FOR UPDATE
, FOR SHARE
, FOR KEY SHARE
Although FOR UPDATE
appears in the SQL standard, the
standard allows it only as an option of DECLARE CURSOR
.
LightDB allows it in any SELECT
query as well as in sub-SELECT
s, but this is an extension.
The FOR NO KEY UPDATE
, FOR SHARE
and
FOR KEY SHARE
variants, as well as the NOWAIT
and SKIP LOCKED
options, do not appear in the
standard.
WITH
LightDB allows INSERT
,
UPDATE
, and DELETE
to be used as WITH
queries. This is not found in the SQL standard.
DISTINCT ON ( ... )
is an extension of the
SQL standard.
ROWS FROM( ... )
is an extension of the SQL standard.
The MATERIALIZED
and NOT
MATERIALIZED
options of WITH
are extensions
of the SQL standard.
You can use '(+)' in where condition to specify outer join like oracle. An example is as follows:
select * from t1 a, t2 b where a.key1(+) = b.key1; QUERY PLAN -------------------------------------------------------------------- Hash Right Join (cost=60.85..86.01 rows=2260 width=48) Hash Cond: (a.key1 = b.key1) -> Seq Scan on t1 a (cost=0.00..22.00 rows=1200 width=40) -> Hash (cost=32.60..32.60 rows=2260 width=8) -> Seq Scan on t2 b (cost=0.00..32.60 rows=2260 width=8) (5 rows)
The following describes the limitations of Oracle (+).
The (+) operator can appear only in the WHERE clause and can be applied only to a column of a table or view.
The (+) operator must match exactly without Spaces. oracle can have spaces.
select * from t1 a, t2 b where a.key1( +) = b.key1; ERROR: syntax error at or near ")" LINE 1: explain select * from t1 a, t2 b where a.key1( +) = b.key1; ^
If A and B are joined by multiple join conditions, you must use the (+) operator in all of these conditions. If you do not, LightDB will return only the rows resulting from a simple join, but without a warning or error to advise you that you do not have the results of an outer join.
explain select * from t1 a, t2 b where a.key1(+)=b.key1 and a.key2=b.key2; QUERY PLAN -------------------------------------------------------------------- Merge Join (cost=317.01..352.19 rows=128 width=16) Merge Cond: ((a.key1 = b.key1) AND (a.key2 = b.key2)) -> Sort (cost=158.51..164.16 rows=2260 width=8) Sort Key: a.key1, a.key2 -> Seq Scan on t1 a (cost=0.00..32.60 rows=2260 width=8) -> Sort (cost=158.51..164.16 rows=2260 width=8) Sort Key: b.key1, b.key2 -> Seq Scan on t2 b (cost=0.00..32.60 rows=2260 width=8) (8 rows)
The (+) operator can be applied only to a column, not to an arbitrary expression. However, an arbitrary expression can contain a column marked with the (+) operator.
select * from t1 a, t2 b where mod(a.key1,10)(+)=b.key1; ERROR: syntax error at or near "(+)" LINE 1: select * from t1 a, t2 b where mod(a.key1,10)(+)=b.key1; ^ select * from t1 a, t2 b where mod(a.key1(+),10)=b.key1; key1 | key2 | key1 | key2 ------+------+------+------ (0 rows)
A condition containing the (+) operator cannot be combined with another condition using the OR logical operator.
select * from t1 a, t2 b where a.key1(+)=b.key1 or a.key2(+)=b.key2; ERROR: Operator "(+)" is not allowed used with "OR" together
A condition cannot compare any column marked with the (+) operator with a subquery.
select * from t1 a, t2 b where a.key1(+)=(select key1 from t3); ERROR: Operator "(+)" can not be used in outer join with SubQuery. LINE 1: select * from t1 a, t2 b where a.key1(+)=(select key1 from t... ^
The tables cannot outer join with each other by using (+).
select * from t1 a, t2 b where a.key1(+)=b.key1 and b.key2(+)=a.key2; ERROR: Relation can't outer join with each other.
The (+) operator cannot be applied to column that belong to table in outer query block.
select * from t1 a where exists (select * from t2 b where a.key1(+)=b.key1); ERROR: Operator "(+)" can't specify on "a" which cannot be referenced from this part of the query. LINE 1: ...rom t1 a where exists (select * from t2 b where a.key1(+)=... ^
The (+) operator cannot be used in nested and/or expression. This is different from oracle, oracle support it.
#oracle also not support it, because it actually is or expression after unnest. select * from t1 a, t2 b where not (a.key1(+)= b.key1 and a.key2(+)=b.key2); ERROR: Operator "(+)" can not be used in nested and/or expression. LINE 1: select * from t1 a, t2 b where not (a.key1(+)= b.key1 and a.... ^ # oracle support 'not (a.key1(+)= b.key1 or a.key2(+)=b.key2)' select * from t1 a, t2 b where not (a.key1(+)= b.key1 or a.key2(+)=b.key2); ERROR: Operator "(+)" can not be used in nested and/or expression. LINE 1: select * from t1 a, t2 b where not (a.key1(+)= b.key1 or a.k... ^
The (+) operator cannot be used with ansi join.
select * from t1 a join t2 b on a.key1=b.key1, t3 c, t4 d where c.key1(+)=d.key1; ERROR: Operator "(+)" and Join in FromClause can't be used together
A table cannot outer join with multiple table. oracle supports this usage.
select * from t1 a, t2 b, t3 c where a.key1(+)=b.key1+c.key1; ERROR: "a" can't outer join with more than one relation HINT: "b", "c" are outer join with "a". select * from t1 a, t2 b, t3 c where a.key1(+)=b.key1 and a.key1(+)=c.key1; ERROR: "a" can't outer join with more than one relation.
The (+) operator cannot be used for full out join.
select * from t1 a, t2 b ,t3 c where a.key1(+) =b.key1(+); ERROR: Operator "(+)" can't be specified on more than one relation in one join condition HINT: "a", "b"...are specified Operator "(+)" in one condition.
Provide examples of how simple pivot
can be used.
create table test123(name varchar(40),chinese int,math int, course varchar(40), score int); insert into test123 values('lisi',88,99,'math',99); insert into test123 values('lisi',88,99,'chinese',88); insert into test123 values('zhangsan',90,100,'chinese',90); insert into test123 values('zhangsan',90,100,'math',100); select * from test123 pivot (sum(score) for course in('chinese','math')); name | chinese | math | 'chinese' | 'math' ----------+---------+------+-----------+-------- lisi | 88 | 99 | 88 | 99 lisi | 89 | 100 | | 99 lisi | 100 | 70 | 100 | zhangsan | 76 | 89 | 99 | zhangsan | 90 | 100 | 90 | 100 zhangsan | 95 | 85 | | 100 (6 rows) drop table test123;
Support querying tables created using double quotesby using table names without double quotes. It can only be used in oracle mode.
create table "TEST123"(name varchar(40),chinese int,math int, course varchar(40), score int); insert into "TEST123" values('lisi',88,99,'math',99); insert into "TEST123" values('lisi',88,99,'chinese',88); insert into "TEST123" values('zhangsan',90,100,'chinese',90); insert into "TEST123" values('zhangsan',90,100,'math',100); select * from test123; ERROR: relation "test123" does not exist LINE 1: select * from test123; ^ set lightdb_oracle_sql_mode = 'selectfrom_tablename_uppercase'; select * from test123; name | chinese | math | course | score ----------+---------+------+---------+------- lisi | 88 | 99 | math | 99 lisi | 88 | 99 | chinese | 88 zhangsan | 90 | 100 | chinese | 90 zhangsan | 90 | 100 | math | 100 (4 rows) drop table test123;