mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-12-13 18:02:24 +00:00
64 lines
2.9 KiB
SQL
64 lines
2.9 KiB
SQL
-- Tags: no-random-merge-tree-settings
|
|
|
|
-- We use a hack - partition by ignore(d1). In some cases there are two columns
|
|
-- not fully correlated (<1) (date_begin - date_end or datetime - datetime_in_TZ_with_DST)
|
|
-- If we partition by these columns instead of one it will be twice more partitions.
|
|
-- Partition by (.., ignore(d1)) allows to partition by the first column but build
|
|
-- min_max indexes for both column, so partition pruning works for both columns.
|
|
-- It's very similar to min_max skip index but gives bigger performance boost,
|
|
-- because partition pruning happens on very early query stage.
|
|
|
|
|
|
DROP TABLE IF EXISTS weird_partitions_02245;
|
|
|
|
CREATE TABLE weird_partitions_02245(d DateTime, d1 DateTime default d - toIntervalHour(8), id Int64)
|
|
Engine=MergeTree
|
|
PARTITION BY (toYYYYMM(toDateTime(d)), ignore(d1))
|
|
ORDER BY id;
|
|
|
|
INSERT INTO weird_partitions_02245(d, id)
|
|
SELECT
|
|
toDateTime('2021-12-31 22:30:00') AS d,
|
|
number
|
|
FROM numbers(1000);
|
|
|
|
INSERT INTO weird_partitions_02245(d, id)
|
|
SELECT
|
|
toDateTime('2022-01-01 00:30:00') AS d,
|
|
number
|
|
FROM numbers(1000);
|
|
|
|
INSERT INTO weird_partitions_02245(d, id)
|
|
SELECT
|
|
toDateTime('2022-01-31 22:30:00') AS d,
|
|
number
|
|
FROM numbers(1000);
|
|
|
|
INSERT INTO weird_partitions_02245(d, id)
|
|
SELECT
|
|
toDateTime('2023-01-31 22:30:00') AS d,
|
|
number
|
|
FROM numbers(1000);
|
|
|
|
OPTIMIZE TABLE weird_partitions_02245;
|
|
OPTIMIZE TABLE weird_partitions_02245;
|
|
|
|
SELECT DISTINCT _partition_id, _partition_value FROM weird_partitions_02245 ORDER BY _partition_id ASC;
|
|
|
|
SELECT _partition_id, min(d), max(d), min(d1), max(d1), count() FROM weird_partitions_02245 GROUP BY _partition_id ORDER BY _partition_id ASC;
|
|
|
|
select DISTINCT _partition_id from weird_partitions_02245 where d >= '2021-12-31 00:00:00' and d < '2022-01-01 00:00:00' ORDER BY _partition_id;
|
|
explain estimate select DISTINCT _partition_id from weird_partitions_02245 where d >= '2021-12-31 00:00:00' and d < '2022-01-01 00:00:00';
|
|
|
|
select DISTINCT _partition_id from weird_partitions_02245 where d >= '2022-01-01 00:00:00' and d1 >= '2021-12-31 00:00:00' and d1 < '2022-01-01 00:00:00' ORDER BY _partition_id;;
|
|
explain estimate select DISTINCT _partition_id from weird_partitions_02245 where d >= '2022-01-01 00:00:00' and d1 >= '2021-12-31 00:00:00' and d1 < '2022-01-01 00:00:00';
|
|
|
|
select DISTINCT _partition_id from weird_partitions_02245 where d1 >= '2021-12-31 00:00:00' and d1 < '2022-01-01 00:00:00' ORDER BY _partition_id;;
|
|
explain estimate select DISTINCT _partition_id from weird_partitions_02245 where d1 >= '2021-12-31 00:00:00' and d1 < '2022-01-01 00:00:00';
|
|
|
|
select DISTINCT _partition_id from weird_partitions_02245 where d >= '2022-01-01 00:00:00' and d1 >= '2021-12-31 00:00:00' and d1 < '2020-01-01 00:00:00' ORDER BY _partition_id;;
|
|
explain estimate select DISTINCT _partition_id from weird_partitions_02245 where d >= '2022-01-01 00:00:00' and d1 >= '2021-12-31 00:00:00' and d1 < '2020-01-01 00:00:00';
|
|
|
|
DROP TABLE weird_partitions_02245;
|
|
|