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

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merged 7 commits into from
Oct 25, 2024
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[Manual Backport] Backport doctest fix to 2.x #3087

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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
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20 changes: 10 additions & 10 deletions docs/user/beyond/partiql.rst
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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
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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 |
+----------------+

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