folding over large BigQuery result - sql

Question

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.

Answer 1

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

Answer 2

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