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_nameAS (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_itemcan be one of: [ ONLY ]table_name[ SAMPLE ( argument ) ] [ * ] [ [ AS ]alias[ (column_alias[, ...] ) ] ]opt_flashback_window_clause[ 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_clausefrom_itemjoin_typefrom_item{ ONjoin_condition| USING (join_column[, ...] ) }from_itemNATURALjoin_typefrom_itemfrom_itemCROSS JOINfrom_itemandgrouping_elementcan be one of: ( )expression(expression[, ...] ) ROLLUP ( {expression| (expression[, ...] ) } [, ...] ) CUBE ( {expression| (expression[, ...] ) } [, ...] ) GROUPING SETS (grouping_element[, ...] ) andwith_queryis:with_query_name[ (column_name[, ...] ) ] AS [ [ NOT ] MATERIALIZED ] (select|values|insert|update|delete) TABLE [ ONLY ]table_name[ * ] andopt_conversion_clauseis:pivot_clause[ * ] [ AS ]aliasandpivot_clauseis: PIVOT (function_name(argument) [ AS ]aliasFORcolumnrefIN (column_definition[, ...] ) ) [ AS ]aliasandopt_flashback_window_clauseis: (AS OF TIMESTAMP expression | VERSIONS BETWEEN TIMESTAMP expression AND expression)
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 rownumis 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_termUNION [ 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_typeOne 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_conditionUSING (,
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, JOINs 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_conditionjoin_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 YY to reference
X.
opt_conversion_clauseis
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 '*'
opt_flashback_window_clause
AS OF TIMESTAMP expression
drop table test_table; create table test_table ( pk int PRIMARY KEY, val int) WITH ( autovacuum_enabled = false); alter table test_table enable flashback; insert into test_table values (1,10); insert into test_table values (2,20); insert into test_table values (3,30); select pg_sleep(1); select pg_sleep(1); select * from test_table; update test_table set val=val+1 where pk=1; update test_table set val=val+1 where pk=2; update test_table set val=val+1 where pk=3; select pg_sleep(1); select * from test_table as of timestamp now() - interval '1 second'; select * from test_table as of timestamp now() - interval '2 seconds';
VERSIONS BETWEEN TIMESTAMP expression AND expression
drop table test_table; create table test_table ( pk int PRIMARY KEY, val int) WITH ( autovacuum_enabled = false); alter table test_table enable flashback; insert into test_table values (1,10); insert into test_table values (2,20); insert into test_table values (3,30); select pg_sleep(1); select pg_sleep(1); select * from test_table; update test_table set val=val+1 where pk=1; update test_table set val=val+1 where pk=2; update test_table set val=val+1 where pk=3; select pg_sleep(1); select * from test_table versions between timestamp now() - interval '1 second' and now(); select * from test_table versions between timestamp now() - interval '3 seconds'and now() - interval '2 seconds';
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 { PRIOR parent_expr = child_expr |
child_expr = PRIOR parent_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_nameAS (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 } BETWEEN frame_start AND frame_end [ frame_exclusion ]
where frame_start
and frame_end can be one of
UNBOUNDED PRECEDINGoffsetPRECEDING CURRENT ROWoffsetFOLLOWING 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_statementUNION [ 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_statementINTERSECT [ 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_statementEXCEPT [ 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 }
OFFSET start
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(...) aliasFROM LATERAL (SELECT .
Note that func(...)) aliasLATERAL 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-SELECTs, 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;