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feat: Support Spark expression years #3405
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| -- Licensed to the Apache Software Foundation (ASF) under one | ||
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| -- Config: spark.sql.catalog.test_cat=org.apache.iceberg.spark.SparkCatalog | ||
| -- Config: spark.sql.catalog.test_cat.type=hadoop | ||
| -- Config: spark.sql.catalog.test_cat.warehouse=/tmp/iceberg-warehouse | ||
| -- Config: spark.comet.scan.icebergNative.enabled=true | ||
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| statement | ||
| CREATE DATABASE IF NOT EXISTS test_cat.db | ||
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| statement | ||
| CREATE TABLE test_cat.db.test_years_iceberg ( | ||
| id INT, | ||
| event_date DATE, | ||
| value STRING | ||
| ) USING iceberg | ||
| PARTITIONED BY (years(event_date)) | ||
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Contributor
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Switching to Parquet throws exception b/c I am not sure how to verify partition pruning is effective on partitioned Iceberg tables. |
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| statement | ||
| INSERT INTO test_cat.db.test_years_iceberg VALUES | ||
| (1, DATE '2022-06-15', 'a'), | ||
| (2, DATE '2023-03-20', 'b'), | ||
| (3, DATE '2023-11-10', 'c'), | ||
| (4, DATE '2024-01-05', 'd'), | ||
| (5, DATE '2024-07-20', 'e'), | ||
| (6, DATE '2024-12-31', 'f') | ||
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| query | ||
| SELECT * FROM test_cat.db.test_years_iceberg ORDER BY id | ||
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| query | ||
| SELECT * FROM test_cat.db.test_years_iceberg WHERE event_date = DATE '2023-03-20' | ||
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| query | ||
| SELECT * FROM test_cat.db.test_years_iceberg WHERE event_date >= DATE '2023-01-01' AND event_date < DATE '2024-01-01' ORDER BY id | ||
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| query | ||
| SELECT year(event_date) as yr, COUNT(*) as cnt FROM test_cat.db.test_years_iceberg GROUP BY year(event_date) ORDER BY yr | ||
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| statement | ||
| DROP TABLE test_cat.db.test_years_iceberg PURGE | ||
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Since
Yearsis aPartitionTransformExpression, maybe we can move it to a new Map(e.g.partitionTransformExpressioninstead of having it intemporalExpressions?