Time series query based on another table - clickhouse

Question

Initial data
CREATE TABLE a_table (
id UInt8,
created_at DateTime
)
ENGINE = MergeTree()
PARTITION BY tuple()
ORDER BY id;
CREATE TABLE b_table (
id UInt8,
started_at DateTime,
stopped_at DateTime
)
ENGINE = MergeTree()
PARTITION BY tuple()
ORDER BY id;
INSERT INTO a_table (id, created_at) VALUES
(1, '2020-01-01 00:00:00'),
(2, '2020-01-02 00:00:00'),
(3, '2020-01-03 00:00:00')
;
INSERT INTO b_table (id, started_at, stopped_at) VALUES
(1, '2020-01-01 00:00:00', '2020-01-01 23:59:59'),
(2, '2020-01-02 00:00:00', '2020-01-02 23:59:59'),
(3, '2020-01-04 00:00:00', '2020-01-04 23:59:59')
;
Expected result: The 'a_table' rows by condition
b_table.started_at >= a_table.created_at AND
b_table.stopped_at <= a_table.created_at
+----+---------------------+
| id | created_at |
+----+---------------------+
| 1 | 2020-01-01 00:00:00 |
+----+---------------------+
| 2 | 2020-01-02 00:00:00 |
+----+---------------------+
What have i tried
-- No errors, empty result
SELECT a_table.*
FROM a_table
INNER JOIN b_table
ON b_table.id = a_table.id
WHERE b_table.started_at >= a_table.created_at
ANd b_table.stopped_at <= a_table.created_at
;
SELECT a_table.*
FROM a_table
ASOF INNER JOIN (
SELECT * FROM b_table
) q
ON q.id = a_table.id
AND q.started_at >= a_table.created_at
-- Error:
-- Invalid expression for JOIN ON.
-- ASOF JOIN expects exactly one inequality in ON section,
-- unexpected stopped_at <= created_at.
-- AND q.stopped_at <= a_table.created_at
;

Answer 1

WHERE b_table.started_at >= a_table.created_at
ANd b_table.stopped_at <= a_table.created_at
Wrong condition >= <= --> <= >=
20.8.7.15
SELECT
a_table.*,
b_table.*
FROM a_table
INNER JOIN b_table ON b_table.id = a_table.id
WHERE (b_table.started_at <= a_table.created_at) AND (b_table.stopped_at >= a_table.created_at)
┌─id─┬──────────created_at─┬─b_table.id─┬──────────started_at─┬──────────stopped_at─┐
│ 1 │ 2020-01-01 00:00:00 │ 1 │ 2020-01-01 00:00:00 │ 2020-01-01 23:59:59 │
│ 2 │ 2020-01-02 00:00:00 │ 2 │ 2020-01-02 00:00:00 │ 2020-01-02 23:59:59 │
└────┴─────────────────────┴────────────┴─────────────────────┴─────────────────────┘
In real production such queries would not work. Because JOIN is very slow.
It needs re-design. It hard to say how without knowing why do you have the second table. Probably I would use rangeHashed external dictionary.