mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-10-03 18:45:35 +00:00
dennis zhuang
affc0a1b1d
* fix: align ordered aggregate state type with the accumulator output Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: reject mismatched aggregate states and keep hard-ordered aggregates unsplit Signed-off-by: Dennis Zhuang <killme2008@gmail.com> * fix: keep WITHIN GROUP aggregates splittable and relabel state fields by position Signed-off-by: Dennis Zhuang <killme2008@gmail.com> --------- Signed-off-by: Dennis Zhuang <killme2008@gmail.com>
95 lines
2.8 KiB
SQL
95 lines
2.8 KiB
SQL
-- Migrated from DuckDB test style: test array aggregation
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-- Test ARRAY_AGG function
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-- Test with integers
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CREATE TABLE integers(i INTEGER, g INTEGER, ts TIMESTAMP TIME INDEX);
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INSERT INTO integers VALUES (1, 1, 1000), (2, 1, 2000), (3, 1, 3000), (4, 2, 4000), (5, 2, 5000);
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-- Basic array aggregation
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SELECT array_agg(i) FROM integers;
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-- Array aggregation with GROUP BY
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SELECT g, array_agg(i) FROM integers GROUP BY g ORDER BY g;
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-- Test with ORDER BY
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SELECT array_agg(i ORDER BY i DESC) FROM integers;
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SELECT g, array_agg(i ORDER BY i DESC) FROM integers GROUP BY g ORDER BY g;
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-- Test with strings
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CREATE TABLE strings(s VARCHAR, g INTEGER, ts TIMESTAMP TIME INDEX);
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INSERT INTO strings VALUES
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('apple', 1, 1000), ('banana', 1, 2000), ('cherry', 2, 3000),
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('date', 2, 4000), ('elderberry', 1, 5000);
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SELECT array_agg(s) FROM strings;
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SELECT g, array_agg(s ORDER BY s) FROM strings GROUP BY g ORDER BY g;
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-- Test with NULL values
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INSERT INTO strings VALUES (NULL, 1, 6000), ('fig', NULL, 7000);
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SELECT array_agg(s) FROM strings WHERE s IS NOT NULL;
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SELECT g, array_agg(s) FROM strings WHERE g IS NOT NULL GROUP BY g ORDER BY g;
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-- Test with DISTINCT
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SELECT array_agg(DISTINCT s ORDER BY s) FROM strings WHERE s IS NOT NULL;
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-- Test empty result
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SELECT array_agg(i) FROM integers WHERE i > 100;
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-- Test with doubles
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CREATE TABLE doubles(d DOUBLE, ts TIMESTAMP TIME INDEX);
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INSERT INTO doubles VALUES (1.1, 1000), (2.2, 2000), (3.3, 3000), (4.4, 4000);
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SELECT array_agg(d ORDER BY d) FROM doubles;
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-- cleanup
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DROP TABLE integers;
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DROP TABLE strings;
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DROP TABLE doubles;
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-- On partitioned tables the aggregate is split into partial state and merge
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CREATE TABLE array_agg_partitioned (
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ts TIMESTAMP TIME INDEX,
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k INT,
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lat DOUBLE,
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PRIMARY KEY(k)
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)
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PARTITION ON COLUMNS (k) (k < 10, k >= 10 AND k < 20, k >= 20);
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INSERT INTO array_agg_partitioned VALUES
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(1000, 1, 1),
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(2000, 11, 2),
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(3000, 21, 3),
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(4000, 2, 4),
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(5000, 12, 5),
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(6000, 22, 6),
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(7000, 3, 7);
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SELECT array_agg(lat ORDER BY ts) FROM array_agg_partitioned;
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SELECT lat > 3 AS g, array_agg(lat ORDER BY ts DESC) FROM array_agg_partitioned GROUP BY g ORDER BY g;
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SELECT array_agg(k ORDER BY k % 10, ts DESC) FROM array_agg_partitioned;
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-- nth_value needs sorted input, so it isn't split into partial state and merge
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SELECT nth_value(lat, 2 ORDER BY ts), nth_value(lat, 3 ORDER BY ts DESC) FROM array_agg_partitioned;
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-- WITHIN GROUP aggregates don't need sorted input and are still split
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-- SQLNESS REPLACE (peers.*) REDACTED
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-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
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-- SQLNESS REPLACE (-+) -
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-- SQLNESS REPLACE (\s\s+) _
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EXPLAIN SELECT sum(lat), approx_percentile_cont(0.75) WITHIN GROUP (ORDER BY lat DESC) FROM array_agg_partitioned;
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SELECT sum(lat), approx_percentile_cont(0.75) WITHIN GROUP (ORDER BY lat DESC) FROM array_agg_partitioned;
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DROP TABLE array_agg_partitioned;
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