feat(spark): implement Spark make_interval function
#17424
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make_interval function
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In spark 3.5 |
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Jefffrey
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Sep 11, 2025
| match length { | ||
| x if x > 7 => { | ||
| exec_err!( | ||
| "make_interval expects between 1 and 7, got {}", |
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| "make_interval expects between 1 and 7, got {}", | |
| "make_interval expects between 0 and 7 arguments, got {}", |
| use arrow::array::AsArray; | ||
| use arrow::datatypes::{Float64Type, Int32Type}; | ||
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| // 0 args is in invoke_with_args |
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Is there a reason that special case isn't handled in here instead?
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| for (i, a) in args.iter().enumerate().skip(1) { | ||
| if a.len() != n_rows { | ||
| return exec_err!( | ||
| "make_dt_interval: argument {i} has length {}, expected {n_rows}", | ||
| a.len() | ||
| ); | ||
| } | ||
| } |
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Do functions usually need to do this check themselves? Is it possible to reach this point where functions are called with arrays of uneven length?
| use datafusion_common::DataFusionError; | ||
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| if !sec.is_finite() { | ||
| return Err(DataFusionError::Execution("seconds is NaN/Inf".into())); |
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| return Err(DataFusionError::Execution("seconds is NaN/Inf".into())); | |
| return Err(DataFusionError::Execution("seconds cannot be NaN or Inf".into())); |
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| // 0 args is in invoke_with_args | ||
| if args.is_empty() || args.len() > 7 { | ||
| return exec_err!("make_interval expects between 0 and 7, got {}", args.len()); |
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| return exec_err!("make_interval expects between 0 and 7, got {}", args.len()); | |
| return exec_err!("make_interval expects between 0 and 7 arguments, got {}", args.len()); |
Though ideally coerce types should already handle this check, I believe
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| let secs_nanos = sec_int | ||
| .checked_mul(1_000_000_000) | ||
| .ok_or_else(|| DataFusionError::Execution("seconds to nanos overflow".into()))?; | ||
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| let total_nanos = hours_nanos | ||
| .checked_add(mins_nanos) | ||
| .and_then(|v| v.checked_add(secs_nanos)) | ||
| .and_then(|v| v.checked_add(frac_nanos)) | ||
| .ok_or_else(|| DataFusionError::Execution("sum nanos overflow".into()))?; |
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I think these error messages could have some more detail to help the user understand exactly what happened
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| # seconds is now blank line | ||
| #query ? | ||
| #SELECT make_interval(0, 0, 0, 0, 0, 0, 0.0); | ||
| #---- | ||
| #0.000000000 secs | ||
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| #query ? | ||
| #SELECT make_interval(); | ||
| #---- | ||
| #0.000000000 secs |
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Is there a plan to uncomment these tests?
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Which issue does this PR close?
part of #15914
Rationale for this change
Migrate spark functions from https://github.com/lakehq/sail/ to datafusion engine to unify codebase
What changes are included in this PR?
implement spark udf make_interval
https://spark.apache.org/docs/latest/api/sql/index.html#make_interval
Are these changes tested?
unit-tests and sqllogictests added
Are there any user-facing changes?
now can be called in queries