perf: optimize spark_hex dictionary path by avoiding dictionary expansion
#19832
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Jefffrey
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Jan 16, 2026
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| let encoded_values_array: ArrayRef = match encoded_values { | ||
| ColumnarValue::Array(a) => a, | ||
| ColumnarValue::Scalar(s) => Arc::new(s.to_array()?), | ||
| }; |
Contributor
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We should probably refactor hex_encode_bytes and hex_encode_int64 to return arrays only, as their signature say they return ColumnarValue but they never return the scalar variant, forcing handling like this
| } | ||
| DataType::Dictionary(_, value_type) => { | ||
| DataType::Dictionary(_, _) => { | ||
| let dict = as_dictionary_array::<Int32Type>(&array); |
Contributor
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nit: we should have some check that the dictionary has i32 key type, otherwise this will panic
| let dict_values = dict.values(); | ||
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| match **value_type { | ||
| let encoded_values: ColumnarValue = match dict_values.data_type() { |
Contributor
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We might want to consider arms for LargeUtf, views, etc.
| FROM VALUES ('foo'), ('bar'), ('foo'), (NULL), ('baz'), ('bar'); | ||
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| query T | ||
| SELECT hex(dict_col) FROM t_dict_utf8; |
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Can we check the output type here with arrow_typeof to ensure they are dictionaries
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Which issue does this PR close?
Follow up to #19738
Rationale for this change
The current hex implementation expands
DictionaryArrayinputs into a regular array, which causes loss of dictionary encoding and redundant hex computation for repeated values.What changes are included in this PR?
Benchmark
Are these changes tested?
Yes. Existing unit tests and
sqllogictesttests pass.Are there any user-facing changes?
No.