Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Manual Backport] Backport doctest fix to 2.x #3087

Merged
merged 7 commits into from
Oct 25, 2024
Merged

[Manual Backport] Backport doctest fix to 2.x #3087

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
722a9a7
Update doctest code for more consistent runs
Swiddis Oct 4, 2024
fa73258
Merge remote-tracking branch 'upstream/2.x' into backport-doctest-fix…
Swiddis Oct 21, 2024
e32de00
Update doctest code for more consistent runs (#3053)
Swiddis Oct 11, 2024
52daa05
Fix doctests
Swiddis Oct 21, 2024
5efb64c
Fix MalformedqueryIT
Swiddis Oct 23, 2024
0a7de6d
Merge remote-tracking branch 'upstream/2.x' into backport-doctest-fix…
Swiddis Oct 23, 2024
f309ff1
Revert "Fix MalformedqueryIT"
Swiddis Oct 23, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 10 additions & 10 deletions docs/user/beyond/partiql.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -202,11 +202,11 @@ Selecting top level for object fields, object fields of array value and nested f

os> SELECT city, accounts, projects FROM people;
fetched rows / total rows = 1/1
+-----------------------------------------------------+------------+----------------------------------------------------------------------------------------------------------------+
| city | accounts | projects |
|-----------------------------------------------------+------------+----------------------------------------------------------------------------------------------------------------|
| {'name': 'Seattle', 'location': {'latitude': 10.5}} | {'id': 1} | [{'name': 'AWS Redshift Spectrum querying'},{'name': 'AWS Redshift security'},{'name': 'AWS Aurora security'}] |
+-----------------------------------------------------+------------+----------------------------------------------------------------------------------------------------------------+
+-----------------------------------------------------+-----------+----------------------------------------------------------------------------------------------------------------+
| city | accounts | projects |
|-----------------------------------------------------+-----------+----------------------------------------------------------------------------------------------------------------|
| {'name': 'Seattle', 'location': {'latitude': 10.5}} | {'id': 1} | [{'name': 'AWS Redshift Spectrum querying'},{'name': 'AWS Redshift security'},{'name': 'AWS Aurora security'}] |
+-----------------------------------------------------+-----------+----------------------------------------------------------------------------------------------------------------+

Example 2: Selecting Deeper Levels
----------------------------------
Expand All @@ -215,11 +215,11 @@ Selecting at deeper levels for object fields of regular value returns inner fiel

os> SELECT city.location, city.location.latitude FROM people;
fetched rows / total rows = 1/1
+--------------------+--------------------------+
| city.location | city.location.latitude |
|--------------------+--------------------------|
| {'latitude': 10.5} | 10.5 |
+--------------------+--------------------------+
+--------------------+------------------------+
| city.location | city.location.latitude |
|--------------------+------------------------|
| {'latitude': 10.5} | 10.5 |
+--------------------+------------------------+


For selecting second level for nested fields, please read on and find more details in the following sections.
Expand Down
216 changes: 108 additions & 108 deletions docs/user/dql/aggregations.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,12 +34,12 @@ The group by expression could be identifier::

os> SELECT gender, sum(age) FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+------------+
| gender | sum(age) |
|----------+------------|
| F | 28 |
| M | 101 |
+----------+------------+
+--------+----------+
| gender | sum(age) |
|--------+----------|
| F | 28 |
| M | 101 |
+--------+----------+


Ordinal
Expand All @@ -49,12 +49,12 @@ The group by expression could be ordinal::

os> SELECT gender, sum(age) FROM accounts GROUP BY 1;
fetched rows / total rows = 2/2
+----------+------------+
| gender | sum(age) |
|----------+------------|
| F | 28 |
| M | 101 |
+----------+------------+
+--------+----------+
| gender | sum(age) |
|--------+----------|
| F | 28 |
| M | 101 |
+--------+----------+


Expression
Expand All @@ -64,14 +64,14 @@ The group by expression could be expression::

os> SELECT abs(account_number), sum(age) FROM accounts GROUP BY abs(account_number);
fetched rows / total rows = 4/4
+-----------------------+------------+
| abs(account_number) | sum(age) |
|-----------------------+------------|
| 1 | 32 |
| 13 | 28 |
| 18 | 33 |
| 6 | 36 |
+-----------------------+------------+
+---------------------+----------+
| abs(account_number) | sum(age) |
|---------------------+----------|
| 1 | 32 |
| 13 | 28 |
| 18 | 33 |
| 6 | 36 |
+---------------------+----------+


Aggregation
Expand All @@ -91,12 +91,12 @@ The aggregation could be used select::

os> SELECT gender, sum(age) FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+------------+
| gender | sum(age) |
|----------+------------|
| F | 28 |
| M | 101 |
+----------+------------+
+--------+----------+
| gender | sum(age) |
|--------+----------|
| F | 28 |
| M | 101 |
+--------+----------+

Expression over Aggregation
---------------------------
Expand All @@ -105,12 +105,12 @@ The aggregation could be used as arguments of expression::

os> SELECT gender, sum(age) * 2 as sum2 FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+--------+
| gender | sum2 |
|----------+--------|
| F | 56 |
| M | 202 |
+----------+--------+
+--------+------+
| gender | sum2 |
|--------+------|
| F | 56 |
| M | 202 |
+--------+------+

Expression as argument of Aggregation
-------------------------------------
Expand All @@ -119,12 +119,12 @@ The aggregation could has expression as arguments::

os> SELECT gender, sum(age * 2) as sum2 FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+--------+
| gender | sum2 |
|----------+--------|
| F | 56 |
| M | 202 |
+----------+--------+
+--------+------+
| gender | sum2 |
|--------+------|
| F | 56 |
| M | 202 |
+--------+------+

COUNT Aggregations
------------------
Expand All @@ -150,12 +150,12 @@ Example::

os> SELECT gender, count(*) as countV FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+----------+
| gender | countV |
|----------+----------|
| F | 1 |
| M | 3 |
+----------+----------+
+--------+--------+
| gender | countV |
|--------+--------|
| F | 1 |
| M | 3 |
+--------+--------+

SUM
---
Expand All @@ -169,12 +169,12 @@ Example::

os> SELECT gender, sum(age) as sumV FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+--------+
| gender | sumV |
|----------+--------|
| F | 28 |
| M | 101 |
+----------+--------+
+--------+------+
| gender | sumV |
|--------+------|
| F | 28 |
| M | 101 |
+--------+------+

AVG
---
Expand All @@ -188,12 +188,12 @@ Example::

os> SELECT gender, avg(age) as avgV FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+--------------------+
| gender | avgV |
|----------+--------------------|
| F | 28.0 |
| M | 33.666666666666664 |
+----------+--------------------+
+--------+--------------------+
| gender | avgV |
|--------+--------------------|
| F | 28.0 |
| M | 33.666666666666664 |
+--------+--------------------+

MAX
---
Expand All @@ -207,11 +207,11 @@ Example::

os> SELECT max(age) as maxV FROM accounts;
fetched rows / total rows = 1/1
+--------+
| maxV |
|--------|
| 36 |
+--------+
+------+
| maxV |
|------|
| 36 |
+------+

MIN
---
Expand All @@ -225,11 +225,11 @@ Example::

os> SELECT min(age) as minV FROM accounts;
fetched rows / total rows = 1/1
+--------+
| minV |
|--------|
| 28 |
+--------+
+------+
| minV |
|------|
| 28 |
+------+

VAR_POP
-------
Expand Down Expand Up @@ -364,11 +364,11 @@ To get the count of distinct values of a field, you can add a keyword ``DISTINCT

os> SELECT COUNT(DISTINCT gender), COUNT(gender) FROM accounts;
fetched rows / total rows = 1/1
+--------------------------+-----------------+
| COUNT(DISTINCT gender) | COUNT(gender) |
|--------------------------+-----------------|
| 2 | 4 |
+--------------------------+-----------------+
+------------------------+---------------+
| COUNT(DISTINCT gender) | COUNT(gender) |
|------------------------+---------------|
| 2 | 4 |
+------------------------+---------------+

PERCENTILE or PERCENTILE_APPROX
-------------------------------
Expand All @@ -382,12 +382,12 @@ Example::

os> SELECT gender, percentile(age, 90) as p90 FROM accounts GROUP BY gender;
fetched rows / total rows = 2/2
+----------+-------+
| gender | p90 |
|----------+-------|
| F | 28 |
| M | 36 |
+----------+-------+
+--------+-----+
| gender | p90 |
|--------+-----|
| F | 28 |
| M | 36 |
+--------+-----+

HAVING Clause
=============
Expand All @@ -413,11 +413,11 @@ Here is an example for typical use of ``HAVING`` clause::
... GROUP BY gender
... HAVING sum(age) > 100;
fetched rows / total rows = 1/1
+----------+------------+
| gender | sum(age) |
|----------+------------|
| M | 101 |
+----------+------------+
+--------+----------+
| gender | sum(age) |
|--------+----------|
| M | 101 |
+--------+----------+

Here is another example for using alias in ``HAVING`` condition. Note that if an identifier is ambiguous, for example present both as a select alias and an index field, preference is alias. This means the identifier will be replaced by expression aliased in ``SELECT`` clause::

Expand All @@ -427,11 +427,11 @@ Here is another example for using alias in ``HAVING`` condition. Note that if an
... GROUP BY gender
... HAVING s > 100;
fetched rows / total rows = 1/1
+----------+-----+
| gender | s |
|----------+-----|
| M | 101 |
+----------+-----+
+--------+-----+
| gender | s |
|--------+-----|
| M | 101 |
+--------+-----+

HAVING without GROUP BY
-----------------------
Expand All @@ -443,11 +443,11 @@ Additionally, a ``HAVING`` clause can work without ``GROUP BY`` clause. This is
... FROM accounts
... HAVING sum(age) > 100;
fetched rows / total rows = 1/1
+------------------------+
| 'Total of age > 100' |
|------------------------|
| Total of age > 100 |
+------------------------+
+----------------------+
| 'Total of age > 100' |
|----------------------|
| Total of age > 100 |
+----------------------+


FILTER Clause
Expand All @@ -465,12 +465,12 @@ The group by aggregation with ``FILTER`` clause can set different conditions for

os> SELECT avg(age) FILTER(WHERE balance > 10000) AS filtered, gender FROM accounts GROUP BY gender
fetched rows / total rows = 2/2
+------------+----------+
| filtered | gender |
|------------+----------|
| 28.0 | F |
| 32.0 | M |
+------------+----------+
+----------+--------+
| filtered | gender |
|----------+--------|
| 28.0 | F |
| 32.0 | M |
+----------+--------+

FILTER without GROUP BY
-----------------------
Expand All @@ -482,11 +482,11 @@ The ``FILTER`` clause can be used in aggregation functions without GROUP BY as w
... count(*) FILTER(WHERE age > 34) AS filtered
... FROM accounts
fetched rows / total rows = 1/1
+--------------+------------+
| unfiltered | filtered |
|--------------+------------|
| 4 | 1 |
+--------------+------------+
+------------+----------+
| unfiltered | filtered |
|------------+----------|
| 4 | 1 |
+------------+----------+

Distinct count aggregate with FILTER
------------------------------------
Expand All @@ -495,9 +495,9 @@ The ``FILTER`` clause is also used in distinct count to do the filtering before

os> SELECT COUNT(DISTINCT firstname) FILTER(WHERE age > 30) AS distinct_count FROM accounts
fetched rows / total rows = 1/1
+------------------+
| distinct_count |
|------------------|
| 3 |
+------------------+
+----------------+
| distinct_count |
|----------------|
| 3 |
+----------------+

Loading
Loading