Related
We have the following table
WITH fake_data(columnA, columnB, columnC) as (
select * from values
(1, 'hello1', 'world18'),
(1, 'hello2', 'world27'),
(2, 'hello9', 'world36')
(3, NULL, 'world35')
(10, 'hello13', 'world5')
)
We convert the entire table into a single column that has a JSON-like structure
CREATE OR REPLACE TEMPORARY TABLE LISTE_JSON (V variant)
AS
WITH COLONNE_KEY
AS (
SELECT
ROW_NUMBER () OVER (ORDER BY columnA DESC) KEY_AUTO
,A.*
FROM fake_data A
),
COLONNE_OBJECT
AS (
SELECT
object_agg(
TO_CHAR(KEY_AUTO ) ,
object_construct(
'columnA', IFNULL(columnA,''),
'columnB', IFNULL(columnB,''),
'columnC', IFNULL(columnC,''),
)
)AS COLONNE_OBJECT
FROM COLONNE_KEY
)
SELECT *
FROM COLONNE_OBJECT;
So far everything is going well.
Now how do I read the variant column through a SELECT and see it as a table, as it was at the beginning?
Ex:
SELECT *
FROM LISTE_JSON
COLUMNA COLUMNB COLUMNC
1 hello1 world18
1 hello2 world27
2 hello9 world36
3 '' world35
10 hello13 world5
You can ether use PIVOT to pull with parts, or you can hand roll the pivot via GROUP BY
SELECT
columna
,max(iff(columnb='hello1', columnc, null)) as hello1
,max(iff(columnb='hello2', columnc, null)) as hello2
,max(iff(columnb='hello3', columnc, null)) as hello3
from table
group by 1 order by 1;
So lets start with working "example code"
WITH fake_data(columnA, columnB, columnC) as (
select * from values
(1, 'hello1', 'world18'),
(1, 'hello2', 'world27'),
(2, 'hello9', 'world36'),
(3, NULL, 'world35'),
(10, 'hello13', 'world5')
), COLONNE_KEY AS (
SELECT
ROW_NUMBER () OVER (ORDER BY columnA DESC) KEY_AUTO
,A.*
FROM fake_data A
), COLONNE_OBJECT AS (
SELECT
object_agg( KEY_AUTO::text ,
object_construct('columnA', IFNULL(columnA::text,''),
'columnB', IFNULL(columnB::text,''),
'columnC', IFNULL(columnC::text,'')
)
)AS COLONNE_OBJECT
FROM COLONNE_KEY
)
SELECT *
FROM COLONNE_OBJECT;
gives:
COLONNE_OBJECT
{ "1": { "columnA": "10", "columnB": "hello13", "columnC": "world5" }, "2": { "columnA": "3", "columnB": "", "columnC": "world35" }, "3": { "columnA": "2", "columnB": "hello9", "columnC": "world36" }, "4": { "columnA": "1", "columnB": "hello1", "columnC": "world18" }, "5": { "columnA": "1", "columnB": "hello2", "columnC": "world27" } }
which you would like to get back into it original table form
thus
SELECT
f.value:"columnA"::number as columna,
f.value:"columnB"::text as columnb,
f.value:"columnC"::text as columnc
FROM COLONNE_OBJECT, table(flatten(input=>colonne_object)) f;
gives you back
COLUMNA
COLUMNB
COLUMNC
10
hello13
world5
3
<empty string>
world35
2
hello9
world36
1
hello1
world18
1
hello2
world27
and the empty string can be swapped back in via
nullif(f.value:"columnB"::text,'') as columnb,
I have an array in Presto and I'd like to count how many times each element occurs in it. For example, I have
[a, a, a, b, b]
and I'd like to get something like
{a: 3, b: 2}
We do not have a direct function for this, but you can combine UNNEST with histogram:
presto> SELECT histogram(x)
-> FROM UNNEST(ARRAY[1111, 1111, 22, 22, 1111]) t(x);
_col0
----------------
{22=2, 1111=3}
You may want to file a new issue for a direct function for this.
SELECT
TRANSFORM_VALUES(
MULTIMAP_FROM_ENTRIES(
TRANSFORM(ARRAY['a', 'a', 'a', 'b', 'b'], x -> ROW(x, 1))
),
(k, v) -> ARRAY_SUM(v)
)
Output:
{
"a": 3,
"b": 2
}
You can use REDUCE if there is no support of ARRAY_SUM:
SELECT
TRANSFORM_VALUES(
MULTIMAP_FROM_ENTRIES(
TRANSFORM(ARRAY['a', 'a', 'a', 'b', 'b'], x -> ROW(x, 1))
),
(k, v) -> REDUCE(v, 0, (s, x) -> s + x, s -> s)
)
In Presto 0.279, you now have a direct function for this purpose. You can easily use array_frequency. The input is your ARRAY, and the output is a MAP, where keys are the element of the given array and values are the frequencies. Fro example, if you run this SQL :
SELECT array_frequency(ARRAY[1,4,1,3,5,4,7,3,1])
The result will be
{
"1": 3,
"3": 2,
"4": 2,
"5": 1,
"7": 1
}
Is there any easy way for me to do something like Ocaml's fold_left on a result of a BigQuery query, where each iteration corresponds to one row in the result?
What product or approach would be the easiest way? It would be great if:
all I need to do is to supply the initial state and the 'folder' function
preferably, I'd like to write the 'folder' function in a functional language
I don't need to install any GCP package
Since I don't know which product or language would work, I cannot be more specific, but pseudocode would be like:
let my_init = []
let my_folder = fun state row ->
// append for now, but it will be complicated. I need to do some set operations here. The point is that I need some way of transferring "state" across rows, when I iterate over rows in a predefined order.
row.col1 :: state
let query = "SELECT col1, col2, col3 FROM table1 ORDER BY timestamp"
query |> List.fold my_folder my_init
The result that I want to get from this simplified example is the final "state".
--- UPDATED ---
There is no bound on the number of rows---if we receive more, we get more rows. Typically, the number is more than a few millions but it can be larger than that.
Here's a simplified example that shows the major problem I'm encountering. We have a table with a few columns:
timestamp
user_id: a string id
operation_json: a stringified JSON object, which is a list of operations, each of which corresponds to either:
add user_id to a set
remove user_id from a set
For example, the followings are valid rows:
----------+---------+----------------------------------------------
timestamp | user_id | operation_json
----------+---------+----------------------------------------------
1 | id1 | [ { "op": "add", "set": "set1" } ]
2 | id2 | [ { "op": "add", "set": "set1" } ]
3 | id1 | [ { "op": "add", "set": "set2" } ]
4 | id3 | [ { "op": "add", "set": "set2" } ]
5 | id1 | [ { "op": "remove", "set": "set1" } ]
----------+---------+----------------------------------------------
As a result, I'd like to get sets of users; i.e.,
set1 |-> { id2 }
set2 |-> { id1, id3 }
I thought fold_left-like operation would be convenient. The state would be map>, and the initial-state would be an empty map.
Below [quick and simple] example for BigQuery Standard SQL
#standardSQL
CREATE TEMP FUNCTION fold(arr ARRAY<INT64>, init INT64)
RETURNS FLOAT64
LANGUAGE js AS """
const reducer = (accumulator, currentValue) => accumulator + parseInt(currentValue);
return arr.reduce(reducer, 5);
""";
WITH `project.dataset.table` AS (
SELECT 1 id, [1, 2, 3, 4] arr, 5 initial_state UNION ALL
SELECT 2, [1, 2, 3, 4, 5, 6, 7], 10
)
SELECT id, fold(arr, initial_state) result
FROM `project.dataset.table`
output is
Row id result
1 1 15.0
2 2 33.0
I think it is self-explanatory enough
See more for JS UDF
folding list of rows
See below extension of above
Here you are assembling array from the result's rows before applying fold function (of course you have some limits for UDF here to have in mind and also on how big your ARRAY of rows can go, etc.
#standardSQL
CREATE TEMP FUNCTION fold(arr ARRAY<INT64>, init INT64)
RETURNS FLOAT64
LANGUAGE js AS """
const reducer = (accumulator, currentValue) => accumulator + parseInt(currentValue);
return arr.reduce(reducer, 5);
""";
WITH `project.dataset.table` AS (
SELECT 1 id, 1 item UNION ALL
SELECT 1, 2 UNION ALL
SELECT 1, 3 UNION ALL
SELECT 1, 4 UNION ALL
SELECT 2, 1 UNION ALL
SELECT 2, 2 UNION ALL
SELECT 2, 3 UNION ALL
SELECT 2, 4 UNION ALL
SELECT 2, 5 UNION ALL
SELECT 2, 6 UNION ALL
SELECT 2, 7
)
SELECT id, fold(ARRAY_AGG(item), 5) result
FROM `project.dataset.table`
GROUP BY id
Note, if you need to include more than one field from each row - you can use ARRAY of STRUCT as below example
ARRAY_AGG(STRUCT(id , item) ORDER by id)
Of course, you will need to adjust respectively signature of fold UDF
For example:
#standardSQL
CREATE TEMP FUNCTION fold(arr ARRAY<STRUCT<id INT64, item INT64>>, init INT64)
RETURNS FLOAT64
LANGUAGE js AS """
const reducer = (accumulator, currentValue) => accumulator + parseInt(currentValue.item);
return arr.reduce(reducer, 5);
""";
WITH `project.dataset.table` AS (
SELECT 1 id, 1 item UNION ALL
SELECT 1, 2 UNION ALL
SELECT 1, 3 UNION ALL
SELECT 1, 4 UNION ALL
SELECT 2, 1 UNION ALL
SELECT 2, 2 UNION ALL
SELECT 2, 3 UNION ALL
SELECT 2, 4 UNION ALL
SELECT 2, 5 UNION ALL
SELECT 2, 6 UNION ALL
SELECT 2, 7
)
SELECT id, fold(ARRAY_AGG(t), 5) result
FROM `project.dataset.table` t
GROUP BY id
Below approach has nothing to do with folding per se, but rather attempt to translate your challenge into set-based one (which is more natural for when you dealing with sql) by identifying the latest op action for each user per set and if it is "remove" just eliminate that user from further consideration - if it is "add" just use the latest "add" for that user / set. This in assumption that there cannot be multiple consecutive "add" action for the same user / set - rather - it can be add /remove / add and so on. of course this can be further adjusted based on real use case
So having above in mind - below example for BigQuery Standard SQL
#standardSQL
WITH `project.dataset.table` AS (
SELECT 1 ts, 'id1' user_id, '[ { "op": "add", "set": "set1" } ]' operation_json UNION ALL
SELECT 2, 'id2', '[ { "op": "add", "set": "set1" } ]' UNION ALL
SELECT 3, 'id1', '[ { "op": "add", "set": "set2" } ]' UNION ALL
SELECT 4, 'id3', '[ { "op": "add", "set": "set2" } ]' UNION ALL
SELECT 5, 'id1', '[ { "op": "remove", "set": "set1" } ]'
)
SELECT bin, STRING_AGG(user_id, ',' ORDER BY ts) result
FROM (
SELECT user_id, bin, ARRAY_AGG(ts ORDER BY ts DESC LIMIT 1)[OFFSET(0)] ts
FROM (
SELECT ts, user_id, op, bin, LAST_VALUE(op) OVER(win) fin
FROM (
SELECT ts, user_id,
JSON_EXTRACT_SCALAR(REGEXP_REPLACE(operation_json, r'^\[|\]$', ''), '$.op') op,
JSON_EXTRACT_SCALAR(REGEXP_REPLACE(operation_json, r'^\[|\]$', ''), '$.set') bin
FROM `project.dataset.table`
)
WINDOW win AS (
PARTITION BY user_id, bin
ORDER BY ts
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
)
WHERE fin = 'add'
GROUP BY user_id, bin
)
GROUP BY bin
-- ORDER BY bin
output is
Row bin result
1 set1 id2
2 set2 id1,id3
if to apply to below dummy data
WITH `project.dataset.table` AS (
SELECT 1 ts, 'id1' user_id, '[ { "op": "add", "set": "set1" } ]' operation_json UNION ALL
SELECT 2, 'id2', '[ { "op": "add", "set": "set1" } ]' UNION ALL
SELECT 3, 'id1', '[ { "op": "add", "set": "set2" } ]' UNION ALL
SELECT 4, 'id3', '[ { "op": "add", "set": "set2" } ]' UNION ALL
SELECT 5, 'id1', '[ { "op": "remove", "set": "set1" } ]' UNION ALL
SELECT 6, 'id1', '[ { "op": "add", "set": "set1" } ]' UNION ALL
SELECT 7, 'id1', '[ { "op": "remove", "set": "set1" } ]' UNION ALL
SELECT 8, 'id1', '[ { "op": "add", "set": "set1" } ]' UNION ALL
SELECT 9, 'id1', '[ { "op": "remove", "set": "set2" } ]' UNION ALL
SELECT 10, 'id1', '[ { "op": "add", "set": "set2" } ]'
)
result will be
Row bin result
1 set1 id2,id1
2 set2 id3,id1
I could really use some help here before my mind explodes...
Given the following data structure:
SELECT * FROM (VALUES (1, 1, 1, 1), (2, 2, 2, 2)) AS t(day, apple, banana, orange);
day | apple | banana | orange
-----+-------+--------+--------
1 | 1 | 1 | 1
2 | 2 | 2 | 2
I want to construct a JSON object which looks like the following:
{
"data": [
{
"day": 1,
"fruits": [
{
"key": "apple",
"value": 1
},
{
"key": "banana",
"value": 1
},
{
"key": "orange",
"value": 1
}
]
}
]
}
Maybe I am not so far away from my goal:
SELECT json_build_object(
'data', json_agg(
json_build_object(
'day', t.day,
'fruits', t)
)
) FROM (VALUES (1, 1, 1, 1), (2, 2, 2, 2)) AS t(day, apple, banana, orange);
Results in:
{
"data": [
{
"day": 1,
"fruits": {
"day": 1,
"apple": 1,
"banana": 1,
"orange": 1
}
}
]
}
I know that there is json_each which may do the trick. But I am struggling to apply it to the query.
Edit:
This is my updated query which, I guess, is pretty close. I have dropped the thought to solve it with json_each. Now I only have to return an array of fruits instead appending to the fruits object:
SELECT json_build_object(
'data', json_agg(
json_build_object(
'day', t.day,
'fruits', json_build_object(
'key', 'apple',
'value', t.apple,
'key', 'banana',
'value', t.banana,
'key', 'orange',
'value', t.orange
)
)
)
) FROM (VALUES (1, 1, 1, 1), (2, 2, 2, 2)) AS t(day, apple, banana, orange);
Would I need to add a subquery to prevent a nested aggregate function?
Use the function jsonb_each() to get pairs (key, value), so you do not have to know the number of columns and their names to get a proper output:
select jsonb_build_object('data', jsonb_agg(to_jsonb(s) order by day))
from (
select day, jsonb_agg(jsonb_build_object('key', key, 'value', value)) as fruits
from (
values (1, 1, 1, 1), (2, 2, 2, 2)
) as t(day, apple, banana, orange),
jsonb_each(to_jsonb(t)- 'day')
group by 1
) s;
The above query gives this object:
{
"data": [
{
"day": 1,
"fruits": [
{
"key": "apple",
"value": 1
},
{
"key": "banana",
"value": 1
},
{
"key": "orange",
"value": 1
}
]
},
{
"day": 2,
"fruits": [
{
"key": "apple",
"value": 2
},
{
"key": "banana",
"value": 2
},
{
"key": "orange",
"value": 2
}
]
}
]
}
Right now, I have an an array that I'm able to select off a table.
[{"_id": 1, "count: 3},{"_id": 2, "count: 14},{"_id": 3, "count: 5}]
From this, I only need the count for a particular _id. For example, I need the count for
_id: 3
I've read the documentation but I haven't been able to figure out the correct way to get the object.
WITH test_array(data) AS ( VALUES
('[
{"_id": 1, "count": 3},
{"_id": 2, "count": 14},
{"_id": 3, "count": 5}
]'::JSONB)
)
SELECT val->>'count' AS result
FROM
test_array ta,
jsonb_array_elements(ta.data) val
WHERE val #> '{"_id":3}'::JSONB;
Result:
result
--------
5
(1 row)