Rich-T-kid opened a new issue, #9841:
URL: https://github.com/apache/arrow-rs/issues/9841

   **Is your feature request related to a problem or challenge? Please describe 
what you are trying to do.**
   There is currently no way to express that a DictionaryArray's values array 
is normalized (i.e., contains no duplicate entries), which leaves meaningful 
computation savings on the table. Several Arrow builders 
(StringDictionaryBuilder, LargeStringDictionaryBuilder, 
BinaryDictionaryBuilder, LargeBinaryDictionaryBuilder) already deduplicate 
their values arrays by construction, but there is currently no way to 
communicate this guarantee to downstream consumers. Knowing whether a 
dictionary's values array is normalized is extremely useful, consumers that 
want to leverage uniqueness guarantees (e.g., for optimized grouping or 
lookups) currently have no cheap way to check this. Verifying normalization 
requires a full linear scan of the entire values array just to confirm 
uniqueness, and that doesn't even account for the logic required to actually 
normalize it if it isn't. This isn't a bug — the Arrow spec does allow 
duplicate values in a dictionary's values array, but the absence of a 
 normalization flag leaves performance on the table in cases where the builder 
already guarantees deduplication. This would be a simple, backwards-compatible 
addition that could meaningfully benefit downstream consumers.
   
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   **Describe the solution you'd like**
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   Add an **is_normalized** boolean flag to DictionaryArray, similar to the 
existing [is_ordered 
flag](https://github.com/apache/arrow-rs/blob/a3dbc154af4b9f6aebf38b4e5343fed176449a8e/arrow-array/src/array/dictionary_array.rs#L256),
 that denotes whether the values array is canonicalized. The change would be 
fully backwards compatible, the flag defaults to false for all existing 
dictionaries, and builders that already guarantee deduplication would set it to 
true at construction time. **_No existing behavior changes._**
   
   **Describe alternatives you've considered**
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   Without this flag, downstream consumers must either perform a linear scan to 
verify uniqueness on every call or make unsafe assumptions about the 
dictionary's structure. Neither is ideal, one is expensive, the other is 
error-prone.
   
   ### Additional context
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   **Downstream Benefits**
   Implementations such as 
[DictionaryCountAccumulator](https://github.com/apache/datafusion/blob/f802ed1c51ad82cb1194d4f2bd3010ec451b2d38/datafusion/functions-aggregate-common/src/aggregate/count_distinct/dict.rs)
 stand to benefit from this improvement as well, currently it simply delegates 
accumulation work to an inner accumulator rather than taking advantage of the 
fact that the values array may already be unique. A normalization flag would 
allow such implementations to short-circuit redundant work entirely.
   On the aggregation side, hash aggregation in particular stands to benefit. 
Work like [#21765](https://github.com/apache/datafusion/pull/21765), which 
introduces a specialized GroupValuesDictionary path that operates directly on 
dictionary structure, could leverage this flag to avoid redundant uniqueness 
checks and unlock further optimizations when the values array is already known 
to be canonical. (also applies to the 2+ column grouping, even more so as the 
normalization cost only increases)
   **Arrow Ecosystem**
   It is also worth noting that widely used Parquet writers, including those in 
Arrow, Spark, and pandas already write deduplicated dictionaries by default. 
This is not forbidden by the spec, meaning normalized dictionaries are already 
common in practice, yet there is no way to communicate that guarantee 
programmatically. This proposal is fully backwards compatible with the [Arrow 
columnar format 
specification](https://github.com/apache/arrow/blob/main/docs/source/format/Columnar.rst)
 — the flag defaults to false for all existing dictionaries, no existing 
behavior changes, and consumers are free to ignore it entirely.
   


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