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Add tests to e_select.test.

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FossilOrigin-Name: 727ced6babf8aca87a69632949a7a0ce9bc2be89
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dan
2010-09-08 19:02:32 +00:00
parent 42262536dd
commit 5c3f58e4df
3 changed files with 522 additions and 141 deletions
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@@ -1,8 +1,5 @@
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1
C Updates\sto\sthe\sdocumentation\sof\sthe\ssqlite3_column_xxxx()\sfamily\sof\s\ninterfaces.\s\sEnhance\ssqlite3_column_blob()\sso\sthat\sit\salways\sreturns\na\sNULL\spointer\sfor\sa\szero-length\sblob.
D 2010-09-08T16:30:36
C Add\stests\sto\se_select.test.
D 2010-09-08T19:02:32
F Makefile.arm-wince-mingw32ce-gcc d6df77f1f48d690bd73162294bbba7f59507c72f
F Makefile.in c599a15d268b1db2aeadea19df2adc3bf2eb6bee
F Makefile.linux-gcc 91d710bdc4998cb015f39edf3cb314ec4f4d7e23
@@ -353,7 +350,7 @@ F test/distinctagg.test 1a6ef9c87a58669438fc771450d7a72577417376
F test/e_expr.test 164e87c1d7b40ceb47c57c3bffa384c81d009aa7
F test/e_fkey.test 6721a741c6499b3ab7e5385923233343c8f1ad05
F test/e_fts3.test 75bb0aee26384ef586165e21018a17f7cd843469
F test/e_select.test 844c606826d19583ca6230575bc9685a4124c19c
F test/e_select.test f84259a15040cd0301e66d1d28b45558e8ab4bcb
F test/enc.test e54531cd6bf941ee6760be041dff19a104c7acea
F test/enc2.test 6d91a5286f59add0cfcbb2d0da913b76f2242398
F test/enc3.test 5c550d59ff31dccdba5d1a02ae11c7047d77c041
@@ -860,14 +857,7 @@ F tool/speedtest2.tcl ee2149167303ba8e95af97873c575c3e0fab58ff
F tool/speedtest8.c 2902c46588c40b55661e471d7a86e4dd71a18224
F tool/speedtest8inst1.c 293327bc76823f473684d589a8160bde1f52c14e
F tool/vdbe-compress.tcl d70ea6d8a19e3571d7ab8c9b75cba86d1173ff0f
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727ced6babf8aca87a69632949a7a0ce9bc2be89

637
test/e_select.test
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@@ -61,6 +61,7 @@ set t1_cross_t1 [list \
# This test runs the SELECT three times - once with:
#
# * s/%JOIN%/,/
# * s/%JOIN%/JOIN/
# * s/%JOIN%/INNER JOIN/
# * s/%JOIN%/CROSS JOIN/
#
@@ -98,38 +99,201 @@ do_catchsql_test e_select-0.1.5 {
#-------------------------------------------------------------------------
# The following tests focus on FROM clause (join) processing.
#
# EVIDENCE-OF: R-26491-65072 If the join-op is a comma (","), then the
# composite dataset is the cartesian product of the sets of records from
# the left and right sides of the join-op.
#
do_execsql_test e_select-1.1.2 { SELECT * FROM t1, t2 } $t1_cross_t2
do_execsql_test e_select-1.1.3 { SELECT * FROM t1 AS x, t1 AS y} $t1_cross_t1
# EVIDENCE-OF: R-22228-15000 If the join-op is a "CROSS JOIN" or "INNER
# JOIN", then the composite dataset is created in the same way as for
# the comma join-op.
# EVIDENCE-OF: R-16074-54196 If the FROM clause is omitted from a simple
# SELECT statement, then the input data is implicitly a single row zero
# columns wide
#
do_execsql_test e_select-1.1.1 { SELECT 'abc' } {abc}
do_execsql_test e_select-1.1.2 { SELECT 'abc' WHERE NULL } {}
do_execsql_test e_select-1.1.3 { SELECT NULL } {{}}
do_execsql_test e_select-1.1.4 { SELECT count(*) } {1}
do_execsql_test e_select-1.1.5 { SELECT count(*) WHERE 0 } {0}
do_execsql_test e_select-1.1.6 { SELECT count(*) WHERE 1 } {1}
# EVIDENCE-OF: R-48114-33255 If there is only a single table in the
# join-source following the FROM clause, then the input data used by the
# SELECT statement is the contents of the named table.
#
# The results of the SELECT queries suggest that they are operating on the
# contents of the table 'xx'.
#
do_execsql_test e_select-1.2.1 {
CREATE TABLE xx(x, y);
INSERT INTO xx VALUES('IiJlsIPepMuAhU', X'10B00B897A15BAA02E3F98DCE8F2');
INSERT INTO xx VALUES(NULL, -16.87);
INSERT INTO xx VALUES(-17.89, 'linguistically');
} {}
do_execsql_test e_select-1.2.2 {
SELECT quote(x), quote(y) FROM xx
} [list \
'IiJlsIPepMuAhU' X'10B00B897A15BAA02E3F98DCE8F2' \
NULL -16.87 \
-17.89 'linguistically' \
]
do_execsql_test e_select-1.2.3 {
SELECT count(*), count(x), count(y) FROM xx
} {3 2 3}
do_execsql_test e_select-1.2.4 {
SELECT sum(x), sum(y) FROM xx
} {-17.89 -16.87}
# EVIDENCE-OF: R-23593-12456 If there is more than one table specified
# as part of the join-source following the FROM keyword, then the
# contents of each named table are joined into a single dataset for the
# simple SELECT statement to operate on.
#
# There are more detailed tests for subsequent requirements that add
# more detail to this idea. We just add a single test that shows that
# data is coming from each of the three tables following the FROM clause
# here to show that the statement, vague as it is, is not incorrect.
#
do_execsql_test e_select-1.3.1 {
SELECT * FROM t1, t2, t3
} [list a one a I a 1 a one a I b 2 a one b II a 1 a one b II b 2 a one c III a 1 a one c III b 2 b two a I a 1 b two a I b 2 b two b II a 1 b two b II b 2 b two c III a 1 b two c III b 2 c three a I a 1 c three a I b 2 c three b II a 1 c three b II b 2 c three c III a 1 c three c III b 2]
#
# The following block of tests - e_select-1.4.* - test that the description
# of cartesian joins in the SELECT documentation is consistent with SQLite.
# In doing so, we test the following three requirements as a side-effect:
#
# EVIDENCE-OF: R-46122-14930 If the join-op is "CROSS JOIN", "INNER
# JOIN", "JOIN" or a comma (",") and there is no ON or USING clause,
# then the result of the join is simply the cartesian product of the
# left and right-hand datasets.
#
# The tests are built on this assertion. Really, they test that the output
# of a CROSS JOIN, JOIN, INNER JOIN or "," join matches the expected result
# of calculating the cartesian product of the left and right-hand datasets.
#
# EVIDENCE-OF: R-46256-57243 There is no difference between the "INNER
# JOIN", "JOIN" and "," join operators.
#
# EVIDENCE-OF: R-07544-24155 The "CROSS JOIN" join operator produces the
# same data as the "INNER JOIN", "JOIN" and "," operators
#
# All tests are run 4 times, with the only difference in each run being
# which of the 4 equivalent cartesian product join operators are used.
# Since the output data is the same in all cases, we consider that this
# qualifies as testing the two statements above.
#
do_execsql_test e_select-1.4.0 {
CREATE TABLE x1(a, b);
CREATE TABLE x2(c, d, e);
CREATE TABLE x3(f, g, h, i);
-- x1: 3 rows, 2 columns
INSERT INTO x1 VALUES(24, 'converging');
INSERT INTO x1 VALUES(NULL, X'CB71');
INSERT INTO x1 VALUES('blonds', 'proprietary');
-- x2: 2 rows, 3 columns
INSERT INTO x2 VALUES(-60.06, NULL, NULL);
INSERT INTO x2 VALUES(-58, NULL, 1.21);
-- x3: 5 rows, 4 columns
INSERT INTO x3 VALUES(-39.24, NULL, 'encompass', -1);
INSERT INTO x3 VALUES('presenting', 51, 'reformation', 'dignified');
INSERT INTO x3 VALUES('conducting', -87.24, 37.56, NULL);
INSERT INTO x3 VALUES('coldest', -96, 'dramatists', 82.3);
INSERT INTO x3 VALUES('alerting', NULL, -93.79, NULL);
} {}
# EVIDENCE-OF: R-59089-25828 The columns of the cartesian product
# dataset are, in order, all the columns of the left-hand dataset
# followed by all the columns of the right-hand dataset.
#
do_join_test e_select-1.4.1.1 {
SELECT * FROM x1 %JOIN% x2 LIMIT 1
} [concat {24 converging} {-60.06 {} {}}]
do_join_test e_select-1.4.1.2 {
SELECT * FROM x2 %JOIN% x1 LIMIT 1
} [concat {-60.06 {} {}} {24 converging}]
do_join_test e_select-1.4.1.3 {
SELECT * FROM x3 %JOIN% x2 LIMIT 1
} [concat {-39.24 {} encompass -1} {-60.06 {} {}}]
do_join_test e_select-1.4.1.4 {
SELECT * FROM x2 %JOIN% x3 LIMIT 1
} [concat {-60.06 {} {}} {-39.24 {} encompass -1}]
# EVIDENCE-OF: R-44414-54710 There is a row in the cartesian product
# dataset formed by combining each unique combination of a row from the
# left-hand and right-hand datasets.
#
do_join_test e_select-1.4.2.1 {
SELECT * FROM x2 %JOIN% x3
} [list -60.06 {} {} -39.24 {} encompass -1 \
-60.06 {} {} presenting 51 reformation dignified \
-60.06 {} {} conducting -87.24 37.56 {} \
-60.06 {} {} coldest -96 dramatists 82.3 \
-60.06 {} {} alerting {} -93.79 {} \
-58 {} 1.21 -39.24 {} encompass -1 \
-58 {} 1.21 presenting 51 reformation dignified \
-58 {} 1.21 conducting -87.24 37.56 {} \
-58 {} 1.21 coldest -96 dramatists 82.3 \
-58 {} 1.21 alerting {} -93.79 {} \
]
# TODO: Come back and add a few more like the above.
# EVIDENCE-OF: R-20659-43267 In other words, if the left-hand dataset
# consists of Nlhs rows of Mlhs columns, and the right-hand dataset of
# Nrhs rows of Mrhs columns, then the cartesian product is a dataset of
# Nlhs.Nrhs rows, each containing Mlhs+Mrhs columns.
#
# x1, x2 (Nlhs=3, Nrhs=2) (Mlhs=2, Mrhs=3)
do_join_test e_select-1.4.3.1 {
SELECT count(*) FROM x1 %JOIN% x2
} [expr 3*2]
do_test e_select-1.4.3.2 {
expr {[llength [execsql {SELECT * FROM x1, x2}]] / 6}
} [expr 2+3]
# x2, x3 (Nlhs=2, Nrhs=5) (Mlhs=3, Mrhs=4)
do_join_test e_select-1.4.3.3 {
SELECT count(*) FROM x2 %JOIN% x3
} [expr 2*5]
do_test e_select-1.4.3.4 {
expr {[llength [execsql {SELECT * FROM x2 JOIN x3}]] / 10}
} [expr 3+4]
# x3, x1 (Nlhs=5, Nrhs=3) (Mlhs=4, Mrhs=2)
do_join_test e_select-1.4.3.5 {
SELECT count(*) FROM x3 %JOIN% x1
} [expr 5*3]
do_test e_select-1.4.3.6 {
expr {[llength [execsql {SELECT * FROM x3 CROSS JOIN x1}]] / 15}
} [expr 4+2]
# x3, x3 (Nlhs=5, Nrhs=5) (Mlhs=4, Mrhs=4)
do_join_test e_select-1.4.3.7 {
SELECT count(*) FROM x3 %JOIN% x3
} [expr 5*5]
do_test e_select-1.4.3.8 {
expr {[llength [execsql {SELECT * FROM x3 INNER JOIN x3 AS x4}]] / 25}
} [expr 4+4]
# Some extra cartesian product tests using tables t1 and t2.
#
do_execsql_test e_select-1.4.4.1 { SELECT * FROM t1, t2 } $t1_cross_t2
do_execsql_test e_select-1.4.4.2 { SELECT * FROM t1 AS x, t1 AS y} $t1_cross_t1
foreach {tn select res} [list \
1 { SELECT * FROM t1 CROSS JOIN t2 } $t1_cross_t2 \
2 { SELECT * FROM t1 AS y CROSS JOIN t1 AS x } $t1_cross_t1 \
3 { SELECT * FROM t1 INNER JOIN t2 } $t1_cross_t2 \
4 { SELECT * FROM t1 AS y INNER JOIN t1 AS x } $t1_cross_t1 \
] {
do_execsql_test e_select-1.2.$tn $select $res
do_execsql_test e_select-1.4.5.$tn $select $res
}
# EVIDENCE-OF: R-00387-12725 If there is an ON clause specified, then
# EVIDENCE-OF: R-45641-53865 If there is an ON clause specified, then
# the ON expression is evaluated for each row of the cartesian product
# and the result cast to a numeric value as if by a CAST expression. All
# rows for which the expression evaluates to NULL or zero (integer value
# 0 or real value 0.0) are excluded from the composite dataset.
#
# Each of the SELECT statements below is executed three times - once with
# the string %JOIN% replaced with a comma, once with "CROSS JOIN" and once
# with "INNER JOIN". The test shows that the results of the query are the
# same in each case.
# 0 or real value 0.0) are excluded from the dataset.
#
foreach {tn select res} [list \
1 { SELECT * FROM t1 %JOIN% t2 ON (1) } $t1_cross_t2 \
@@ -239,12 +403,11 @@ foreach {tn select res} {
do_join_test e_select-1.7.$tn $select $res
}
# EVIDENCE-OF: R-04095-00676 If the join-op is a "LEFT JOIN" or "LEFT
# OUTER JOIN", then the composite dataset is created as for an "INNER
# JOIN". Except, after the ON or USING filtering clauses have been
# EVIDENCE-OF: R-41434-12448 If the join-op is a "LEFT JOIN" or "LEFT
# OUTER JOIN", then after the ON or USING filtering clauses have been
# applied, an extra row is added to the output for each row in the
# original left-hand input dataset (if any) that corresponds to no rows
# at all in the composite dataset.
# original left-hand input dataset that corresponds to no rows at all in
# the composite dataset (if any).
#
do_execsql_test e_select-1.8.0 {
CREATE TABLE t7(a, b, c);
@@ -355,17 +518,130 @@ foreach {tn sql} {
" {1 {a NATURAL join may not have an ON or USING clause}}
}
#-------------------------------------------------------------------------
# te_* commands:
#
#
# te_read_sql DB SELECT-STATEMENT
# te_read_tbl DB TABLENAME
#
# These two commands are used to read a dataset from the database. A dataset
# consists of N rows of M named columns of values each, where each value has a
# type (null, integer, real, text or blob) and a value within the types domain.
# The tcl format for a "dataset" is a list of two elements:
#
# * A list of the column names.
# * A list of data rows. Each row is itself a list, where each element is
# the contents of a column of the row. Each of these is a list of two
# elements, the type name and the actual value.
#
# For example, the contents of table [t1] as a dataset is:
#
# CREATE TABLE t1(a, b);
# INSERT INTO t1 VALUES('abc', NULL);
# INSERT INTO t1 VALUES(43.1, 22);
#
# {a b} {{{TEXT abc} {NULL {}}} {{REAL 43.1} {INTEGER 22}}}
#
# The [te_read_tbl] command returns a dataset read from a table. The
# [te_read_sql] returns the dataset that results from executing a SELECT
# command.
#
#
# te_tbljoin ?SWITCHES? LHS-TABLE RHS-TABLE
# te_join ?SWITCHES? LHS-DATASET RHS-DATASET
#
# This command joins the two datasets and returns the resulting dataset. If
# there are no switches specified, then the results is the cartesian product
# of the two inputs. The [te_tbljoin] command reads the left and right-hand
# datasets from the specified tables. The [te_join] command is passed the
# datasets directly.
#
# Optional switches are as follows:
#
# -on SCRIPT
# -using COLUMN-LIST
# -left
#
# The -on option specifies a tcl script that is executed for each row in the
# cartesian product of the two datasets. The script has 4 arguments appended
# to it, in the following order:
#
# * The list of column-names from the left-hand dataset.
# * A single row from the left-hand dataset (one "data row" list as
# described above.
# * The list of column-names from the right-hand dataset.
# * A single row from the right-hand dataset.
#
# The script must return a boolean value - true if the combination of rows
# should be included in the output dataset, or false otherwise.
#
# The -using option specifies a list of the columns from the right-hand
# dataset that should be omitted from the output dataset.
#
# If the -left option is present, the join is done LEFT JOIN style.
# Specifically, an extra row is inserted if after the -on script is run there
# exist rows in the left-hand dataset that have no corresponding rows in
# the output. See the implementation for more specific comments.
#
#
# te_equals ?SWITCHES? COLNAME1 COLNAME2 <-on script args>
#
# The only supported switch is "-nocase". If it is present, then text values
# are compared in a case-independent fashion. Otherwise, they are compared
# as if using the SQLite BINARY collation sequence.
#
#
# te_and ONSCRIPT1 ONSCRIPT2...
#
#
#
# te_read_tbl DB TABLENAME
# te_read_sql DB SELECT-STATEMENT
#
# These two procs are used to extract datasets from the database, either
# by reading the contents of a named table (te_read_tbl), or by executing
# a SELECT statement (t3_read_sql).
#
# See the comment above, describing "te_* commands", for details of the
# return values.
#
proc te_read_tbl {db tbl} {
te_read_sql $db "SELECT * FROM $tbl"
}
proc te_read_sql {db sql} {
set S [sqlite3_prepare_v2 $db $sql -1 DUMMY]
set cols [list]
for {set i 0} {$i < [sqlite3_column_count $S]} {incr i} {
lappend cols [sqlite3_column_name $S $i]
}
set rows [list]
while {[sqlite3_step $S] == "SQLITE_ROW"} {
set r [list]
for {set i 0} {$i < [sqlite3_column_count $S]} {incr i} {
lappend r [list [sqlite3_column_type $S $i] [sqlite3_column_text $S $i]]
}
lappend rows $r
}
sqlite3_finalize $S
return [list $cols $rows]
}
#-------
# Usage: tcl_join <table-data1> <table-data2> <join spec>...
# Usage: te_join <table-data1> <table-data2> <join spec>...
#
# Where a join-spec is an optional list of arguments as follows:
#
# ?-left?
# ?-using colname-list using-expr-proc?
# ?-left?
# ?-using colname-list?
# ?-on on-expr-proc?
#
proc tcl_join {data1 data2 args} {
proc te_join {data1 data2 args} {
set testproc ""
set usinglist [list]
@@ -373,14 +649,9 @@ proc tcl_join {data1 data2 args} {
for {set i 0} {$i < [llength $args]} {incr i} {
set a [lindex $args $i]
switch -- $a {
-on { set testproc [lindex $args [incr i]] }
-using {
set usinglist [lindex $args [incr i]]
}
-left {
set isleft 1
}
-on { set testproc [lindex $args [incr i]] }
-using { set usinglist [lindex $args [incr i]] }
-left { set isleft 1 }
default {
error "Unknown argument: $a"
}
@@ -429,8 +700,8 @@ proc tcl_join {data1 data2 args} {
list $cret $rret
}
proc tcl_tbljoin {db t1 t2 args} {
tcl_join [tcl_read_tbl $db $t1] [tcl_read_tbl $db $t2] {*}$args
proc te_tbljoin {db t1 t2 args} {
te_join [te_read_tbl $db $t1] [te_read_tbl $db $t2] {*}$args
}
#----------
@@ -454,8 +725,8 @@ proc te_equals {args} {
}
}
set idx1 [lsearch $cols1 $c1]
set idx2 [lsearch $cols2 $c2]
set idx2 [if {[string is integer $c2]} { set c2 } else { lsearch $cols2 $c2 }]
set idx1 [if {[string is integer $c1]} { set c1 } else { lsearch $cols1 $c1 }]
set t1 [lindex $row1 $idx1 0]
set t2 [lindex $row2 $idx2 0]
@@ -468,6 +739,9 @@ proc te_equals {args} {
return [expr {$t1 == $t2 && $v1 == $v2}]
}
proc te_false {args} { return 0 }
proc te_true {args} { return 1 }
proc te_and {args} {
foreach a [lrange $args 0 end-4] {
set res [eval $a [lrange $args end-3 end]]
@@ -476,36 +750,32 @@ proc te_and {args} {
return 1
}
# Read the
#
# Table data format:
#
# * List of column names.
#
# * List of rows. Each row is a list of values. Each value is a list of
# 2 elements - the value type and string representation.
#
proc tcl_read_tbl {db tbl} { tcl_read_sql $db "SELECT * FROM $tbl" }
proc tcl_read_sql {db sql} {
set S [sqlite3_prepare_v2 $db $sql -1 DUMMY]
proc te_dataset_eq {testname got expected} {
uplevel #0 [list do_test $testname [list set {} $got] $expected]
}
proc te_dataset_eq_unordered {testname got expected} {
lset got 1 [lsort [lindex $got 1]]
lset expected 1 [lsort [lindex $expected 1]]
te_dataset_eq $testname $got $expected
}
set cols [list]
for {set i 0} {$i < [sqlite3_column_count $S]} {incr i} {
lappend cols [sqlite3_column_name $S $i]
}
proc te_dataset_ne {testname got unexpected} {
uplevel #0 [list do_test $testname [list string equal $got $unexpected] 0]
}
proc te_dataset_ne_unordered {testname got unexpected} {
lset got 1 [lsort [lindex $got 1]]
lset unexpected 1 [lsort [lindex $unexpected 1]]
te_dataset_ne $testname $got $unexpected
}
set rows [list]
while {[sqlite3_step $S] == "SQLITE_ROW"} {
set r [list]
for {set i 0} {$i < [sqlite3_column_count $S]} {incr i} {
lappend r [list [sqlite3_column_type $S $i] [sqlite3_column_text $S $i]]
}
lappend rows $r
}
sqlite3_finalize $S
return [list $cols $rows]
#-------------------------------------------------------------------------
#
proc test_join {tn sqljoin tbljoinargs} {
set sql [te_read_sql db "SELECT * FROM $sqljoin"]
set te [te_tbljoin db {*}$tbljoinargs]
te_dataset_eq_unordered $tn $sql $te
}
drop_all_tables
@@ -514,80 +784,201 @@ do_execsql_test e_select-2.0 {
CREATE TABLE t2(a, b);
CREATE TABLE t3(b COLLATE nocase);
INSERT INTO t1 VALUES(1, 'A');
INSERT INTO t1 VALUES(2, 'B');
INSERT INTO t1 VALUES(3, NULL);
INSERT INTO t1 VALUES(1, 'A');
INSERT INTO t1 VALUES(4, 'D');
INSERT INTO t1 VALUES(NULL, NULL);
INSERT INTO t1 VALUES(3, NULL);
INSERT INTO t2 VALUES(1, 'A');
INSERT INTO t2 VALUES(2, NULL);
INSERT INTO t2 VALUES(3, 'C');
INSERT INTO t2 VALUES(5, 'E');
INSERT INTO t2 VALUES(NULL, NULL);
INSERT INTO t2 VALUES(3, 'C');
INSERT INTO t3 VALUES('a');
INSERT INTO t3 VALUES('b');
INSERT INTO t3 VALUES('c');
INSERT INTO t3 VALUES('b');
} {}
foreach {tn sqljoin tbljoinargs} {
1 "t1, t2" {t1 t2}
2 "t1, t2 ON (t1.a=t2.a)" {t1 t2 -on {te_equals a a}}
3 "t1 LEFT JOIN t2 ON (t1.a=t2.a)" {t1 t2 -left -on {te_equals a a}}
4 "t1 LEFT JOIN t2 USING (a)"
{t1 t2 -left -using a -on {te_equals a a}}
5 "t1 CROSS JOIN t2 USING(b, a)"
{t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
6 "t1 NATURAL JOIN t2"
{t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
7 "t1 NATURAL INNER JOIN t2"
{t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
8 "t1 NATURAL CROSS JOIN t2"
{t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
9 "t1 NATURAL INNER JOIN t2"
{t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
10 "t1 NATURAL LEFT JOIN t2"
{t1 t2 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
11 "t1 NATURAL LEFT OUTER JOIN t2"
{t1 t2 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
12 "t2 NATURAL JOIN t1"
{t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
13 "t2 NATURAL INNER JOIN t1"
{t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
14 "t2 NATURAL CROSS JOIN t1"
{t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
15 "t2 NATURAL INNER JOIN t1"
{t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
16 "t2 NATURAL LEFT JOIN t1"
{t2 t1 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
17 "t2 NATURAL LEFT OUTER JOIN t1"
{t2 t1 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}}
18 "t1 LEFT JOIN t2 USING (b)"
{t1 t2 -left -using b -on {te_equals b b}}
19 "t1 JOIN t3 USING(b)" {t1 t3 -using b -on {te_equals b b}}
20 "t3 JOIN t1 USING(b)" {t3 t1 -using b -on {te_equals -nocase b b}}
21 "t1 NATURAL JOIN t3" {t1 t3 -using b -on {te_equals b b}}
22 "t3 NATURAL JOIN t1" {t3 t1 -using b -on {te_equals -nocase b b}}
23 "t1 NATURAL LEFT JOIN t3" {t1 t3 -left -using b -on {te_equals b b}}
24 "t3 NATURAL LEFT JOIN t1"
{t3 t1 -left -using b -on {te_equals -nocase b b}}
25 "t1 LEFT JOIN t3 ON (t3.b=t1.b)"
{t1 t3 -left -on {te_equals -nocase b b}}
26 "t1 LEFT JOIN t3 ON (t1.b=t3.b)"
{t1 t3 -left -on {te_equals b b}}
foreach {tn indexes} {
e_select-2.1 { }
e_select-2.2 { CREATE INDEX i1 ON t1(a) }
e_select-2.3 { CREATE INDEX i1 ON t2(a) }
e_select-2.4 { CREATE INDEX i1 ON t3(b) }
} {
do_test e_select-2.1.$tn [list tcl_read_sql db "SELECT * FROM $sqljoin"
] [tcl_tbljoin db {*}$tbljoinargs]
catchsql { DROP INDEX i1 }
catchsql { DROP INDEX i2 }
catchsql { DROP INDEX i3 }
execsql $indexes
# EVIDENCE-OF: R-46122-14930 If the join-op is "CROSS JOIN", "INNER
# JOIN", "JOIN" or a comma (",") and there is no ON or USING clause,
# then the result of the join is simply the cartesian product of the
# left and right-hand datasets.
#
# EVIDENCE-OF: R-46256-57243 There is no difference between the "INNER
# JOIN", "JOIN" and "," join operators.
#
# EVIDENCE-OF: R-07544-24155 The "CROSS JOIN" join operator produces the
# same data as the "INNER JOIN", "JOIN" and "," operators
#
test_join $tn.1.1 "t1, t2" {t1 t2}
test_join $tn.1.2 "t1 INNER JOIN t2" {t1 t2}
test_join $tn.1.3 "t1 CROSS JOIN t2" {t1 t2}
test_join $tn.1.4 "t1 JOIN t2" {t1 t2}
test_join $tn.1.5 "t2, t3" {t2 t3}
test_join $tn.1.6 "t2 INNER JOIN t3" {t2 t3}
test_join $tn.1.7 "t2 CROSS JOIN t3" {t2 t3}
test_join $tn.1.8 "t2 JOIN t3" {t2 t3}
test_join $tn.1.9 "t2, t2 AS x" {t2 t2}
test_join $tn.1.10 "t2 INNER JOIN t2 AS x" {t2 t2}
test_join $tn.1.11 "t2 CROSS JOIN t2 AS x" {t2 t2}
test_join $tn.1.12 "t2 JOIN t2 AS x" {t2 t2}
# EVIDENCE-OF: R-45641-53865 If there is an ON clause specified, then
# the ON expression is evaluated for each row of the cartesian product
# and the result cast to a numeric value as if by a CAST expression. All
# rows for which the expression evaluates to NULL or zero (integer value
# 0 or real value 0.0) are excluded from the dataset.
#
test_join $tn.2.1 "t1, t2 ON (t1.a=t2.a)" {t1 t2 -on {te_equals a a}}
test_join $tn.2.2 "t2, t1 ON (t1.a=t2.a)" {t2 t1 -on {te_equals a a}}
test_join $tn.2.3 "t2, t1 ON (1)" {t2 t1 -on te_true}
test_join $tn.2.4 "t2, t1 ON (NULL)" {t2 t1 -on te_false}
test_join $tn.2.5 "t2, t1 ON (1.1-1.1)" {t2 t1 -on te_false}
test_join $tn.2.6 "t1, t2 ON (1.1-1.0)" {t1 t2 -on te_true}
test_join 3 "t1 LEFT JOIN t2 ON (t1.a=t2.a)" {t1 t2 -left -on {te_equals a a}}
test_join 4 "t1 LEFT JOIN t2 USING (a)" {
t1 t2 -left -using a -on {te_equals a a}
}
test_join 5 "t1 CROSS JOIN t2 USING(b, a)" {
t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 6 "t1 NATURAL JOIN t2" {
t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 7 "t1 NATURAL INNER JOIN t2" {
t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 8 "t1 NATURAL CROSS JOIN t2" {
t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 9 "t1 NATURAL INNER JOIN t2" {
t1 t2 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 10 "t1 NATURAL LEFT JOIN t2" {
t1 t2 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 11 "t1 NATURAL LEFT OUTER JOIN t2" {
t1 t2 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 12 "t2 NATURAL JOIN t1" {
t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 13 "t2 NATURAL INNER JOIN t1" {
t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 14 "t2 NATURAL CROSS JOIN t1" {
t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 15 "t2 NATURAL INNER JOIN t1" {
t2 t1 -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 16 "t2 NATURAL LEFT JOIN t1" {
t2 t1 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 17 "t2 NATURAL LEFT OUTER JOIN t1" {
t2 t1 -left -using {a b} -on {te_and {te_equals a a} {te_equals b b}}
}
test_join 18 "t1 LEFT JOIN t2 USING (b)" {
t1 t2 -left -using b -on {te_equals b b}
}
test_join 19 "t1 JOIN t3 USING(b)" {t1 t3 -using b -on {te_equals b b}}
test_join 20 "t3 JOIN t1 USING(b)" {
t3 t1 -using b -on {te_equals -nocase b b}
}
test_join 21 "t1 NATURAL JOIN t3" {
t1 t3 -using b -on {te_equals b b}
}
test_join 22 "t3 NATURAL JOIN t1" {
t3 t1 -using b -on {te_equals -nocase b b}
}
test_join 23 "t1 NATURAL LEFT JOIN t3" {
t1 t3 -left -using b -on {te_equals b b}
}
test_join 24 "t3 NATURAL LEFT JOIN t1" {
t3 t1 -left -using b -on {te_equals -nocase b b}
}
test_join 25 "t1 LEFT JOIN t3 ON (t3.b=t1.b)" {
t1 t3 -left -on {te_equals -nocase b b}
}
test_join 26 "t1 LEFT JOIN t3 ON (t1.b=t3.b)" {
t1 t3 -left -on {te_equals b b}
}
test_join 27 "t1 JOIN t3 ON (t1.b=t3.b)" { t1 t3 -on {te_equals b b} }
# EVIDENCE-OF: R-28760-53843 When more than two tables are joined
# together as part of a FROM clause, the join operations are processed
# in order from left to right. In other words, the FROM clause (A
# join-op-1 B join-op-2 C) is computed as ((A join-op-1 B) join-op-2 C).
#
# Tests 28a and 28b show that the statement above is true for this case.
# Test 28c shows that if the parenthesis force a different order of
# evaluation the result is different. Test 28d verifies that the result
# of the query with the parenthesis forcing a different order of evaluation
# is as calculated by the [te_*] procs.
#
set t3_natural_left_join_t2 [
te_tbljoin db t3 t2 -left -using {b} -on {te_equals -nocase b b}
]
set t1 [te_read_tbl db t1]
te_dataset_eq_unordered $tn.28a [
te_read_sql db "SELECT * FROM t3 NATURAL LEFT JOIN t2 NATURAL JOIN t1"
] [te_join $t3_natural_left_join_t2 $t1 \
-using {a b} -on {te_and {te_equals a a} {te_equals -nocase b b}} \
]
te_dataset_eq_unordered $tn.28b [
te_read_sql db "SELECT * FROM (t3 NATURAL LEFT JOIN t2) NATURAL JOIN t1"
] [te_join $t3_natural_left_join_t2 $t1 \
-using {a b} -on {te_and {te_equals a a} {te_equals -nocase b b}} \
]
te_dataset_ne_unordered $tn.28c [
te_read_sql db "SELECT * FROM (t3 NATURAL LEFT JOIN t2) NATURAL JOIN t1"
] [
te_read_sql db "SELECT * FROM t3 NATURAL LEFT JOIN (t2 NATURAL JOIN t1)"
]
set t2_natural_join_t1 [te_tbljoin db t2 t1 -using {a b} \
-using {a b} -on {te_and {te_equals a a} {te_equals -nocase b b}} \
]
set t3 [te_read_tbl db t3]
te_dataset_eq_unordered $tn.28d [
te_read_sql db "SELECT * FROM t3 NATURAL LEFT JOIN (t2 NATURAL JOIN t1)"
] [te_join $t3 $t2_natural_join_t1 \
-left -using {b} -on {te_equals -nocase b b} \
]
}
# XXXEVIDENCE-OF: R-55824-40976 A sub-select specified in the join-source
# following the FROM clause in a simple SELECT statement is handled as
# if it was a table containing the data returned by executing the
# sub-select statement.
#
proc test_subselect_join {tn subselect select script} {
1 "SELECT * FROM t2" "SELECT * FROM t1 JOIN (%ss%)"
{t1 %ss%}
} {
execsql "CREATE TEMP TABLE sstemp AS $subselect"
set ssdata [te_read_tbl db sstemp]
execsql "DROP TABLE sstemp"
}
finish_test