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bb50514a00
* Update test data for `tests.integration.trino` This is to create tables with complex data types. Using raw SQL because creating tables with pandas didn't get the right types for the structs * Update tests to reproduce the issue Also included the new tables in the other tests to make sure complex data types do not break anything else Reference: [issue 16983](https://github.com/open-metadata/OpenMetadata/issues/16983) * Added `TypeDecorator`s handle `trino.types.NamedRowTuple` This is because pydantic couldn't figure out how to create python objects when receiving `NamedRowTuple`s, which broke the sampling process. This makes sure the data we receive from the trino interface is compatible with Pydantic
68 lines
1.7 KiB
SQL
68 lines
1.7 KiB
SQL
CREATE TABLE IF NOT EXISTS {catalog}.{schema}.{table_name} (
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promotiontransactionid BIGINT,
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validto TIMESTAMP,
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vouchercode VARCHAR,
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payload ROW(
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id VARCHAR,
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amount DOUBLE,
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currency VARCHAR,
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metadata MAP(VARCHAR, VARCHAR),
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items ARRAY(ROW(
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itemId VARCHAR,
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quantity INTEGER,
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price DOUBLE
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))
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),
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adjustmenthistory ARRAY(ROW(
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adjustmentId VARCHAR,
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timestamp TIMESTAMP,
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amount DOUBLE,
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reason VARCHAR
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)),
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simplemap MAP(VARCHAR, VARCHAR),
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simplearray ARRAY(VARCHAR)
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);
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INSERT INTO {catalog}.{schema}.{table_name} VALUES
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(
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1001,
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TIMESTAMP '2024-12-31 23:59:59',
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'PROMO2024',
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ROW(
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'txn_001',
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99.99,
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'USD',
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MAP(ARRAY['store', 'region'], ARRAY['Store123', 'US-West']),
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ARRAY[
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ROW('item_001', 2, 29.99),
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ROW('item_002', 1, 40.01)
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]
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),
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ARRAY[
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ROW('adj_001', TIMESTAMP '2024-01-15 10:30:00', -5.00, 'Discount'),
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ROW('adj_002', TIMESTAMP '2024-01-15 11:00:00', 2.50, 'Tax adjustment')
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],
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MAP(ARRAY['status', 'type'], ARRAY['active', 'promotion']),
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ARRAY['tag1', 'tag2', 'tag3']
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),
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(
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1002,
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TIMESTAMP '2024-06-30 23:59:59',
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'SUMMER2024',
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ROW(
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'txn_002',
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150.75,
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'EUR',
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MAP(ARRAY['campaign', 'channel'], ARRAY['Summer Sale', 'Online']),
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ARRAY[
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ROW('item_003', 3, 45.25),
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ROW('item_004', 1, 15.00)
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]
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),
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ARRAY[
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ROW('adj_003', TIMESTAMP '2024-02-20 14:15:00', -10.00, 'Coupon')
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],
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MAP(ARRAY['status', 'priority'], ARRAY['completed', 'high']),
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ARRAY['summer', 'sale', 'online']
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)
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