parquet/arrow/arrow_writer/

byte_array.rs

// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

use crate::basic::Encoding;
use crate::bloom_filter::Sbbf;
use crate::column::writer::encoder::{
    ColumnValueEncoder, DataPageValues, DictionaryPage, create_bloom_filter,
};
use crate::data_type::{AsBytes, ByteArray, Int32Type};
use crate::encodings::encoding::{DeltaBitPackEncoder, Encoder};
use crate::encodings::rle::RleEncoder;
use crate::errors::{ParquetError, Result};
use crate::file::properties::{
    EnabledStatistics, ResolvedColumnProperties, WriterProperties, WriterVersion,
};
use crate::geospatial::accumulator::{GeoStatsAccumulator, try_new_geo_stats_accumulator};
use crate::geospatial::statistics::GeospatialStatistics;
use crate::schema::types::ColumnDescPtr;
use crate::util::bit_util::num_required_bits;
use crate::util::interner::{Interner, Storage};
use crate::util::prefix::common_prefix_length;
use arrow_array::types::ByteArrayType;
use arrow_array::{
    Array, ArrayAccessor, BinaryArray, BinaryViewArray, DictionaryArray, FixedSizeBinaryArray,
    GenericByteArray, LargeBinaryArray, LargeStringArray, StringArray, StringViewArray,
};
use arrow_buffer::{ArrowNativeType, Buffer};
use arrow_schema::DataType;

macro_rules! downcast_dict_impl {
    ($array:ident, $key:ident, $val:ident, $op:expr $(, $arg:expr)*) => {{
        $op($array
            .as_any()
            .downcast_ref::<DictionaryArray<arrow_array::types::$key>>()
            .unwrap()
            .downcast_dict::<$val>()
            .unwrap()$(, $arg)*)
    }};
}

macro_rules! downcast_dict_op {
    ($key_type:expr, $val:ident, $array:ident, $op:expr $(, $arg:expr)*) => {
        match $key_type.as_ref() {
            DataType::UInt8 => downcast_dict_impl!($array, UInt8Type, $val, $op$(, $arg)*),
            DataType::UInt16 => downcast_dict_impl!($array, UInt16Type, $val, $op$(, $arg)*),
            DataType::UInt32 => downcast_dict_impl!($array, UInt32Type, $val, $op$(, $arg)*),
            DataType::UInt64 => downcast_dict_impl!($array, UInt64Type, $val, $op$(, $arg)*),
            DataType::Int8 => downcast_dict_impl!($array, Int8Type, $val, $op$(, $arg)*),
            DataType::Int16 => downcast_dict_impl!($array, Int16Type, $val, $op$(, $arg)*),
            DataType::Int32 => downcast_dict_impl!($array, Int32Type, $val, $op$(, $arg)*),
            DataType::Int64 => downcast_dict_impl!($array, Int64Type, $val, $op$(, $arg)*),
            _ => unreachable!(),
        }
    };
}

macro_rules! downcast_op {
    ($data_type:expr, $array:ident, $op:expr $(, $arg:expr)*) => {
        match $data_type {
            DataType::Utf8 => $op($array.as_any().downcast_ref::<StringArray>().unwrap()$(, $arg)*),
            DataType::LargeUtf8 => {
                $op($array.as_any().downcast_ref::<LargeStringArray>().unwrap()$(, $arg)*)
            }
            DataType::Utf8View => $op($array.as_any().downcast_ref::<StringViewArray>().unwrap()$(, $arg)*),
            DataType::Binary => {
                $op($array.as_any().downcast_ref::<BinaryArray>().unwrap()$(, $arg)*)
            }
            DataType::LargeBinary => {
                $op($array.as_any().downcast_ref::<LargeBinaryArray>().unwrap()$(, $arg)*)
            }
            DataType::BinaryView => {
                $op($array.as_any().downcast_ref::<BinaryViewArray>().unwrap()$(, $arg)*)
            }
            DataType::Dictionary(key, value) => match value.as_ref() {
                DataType::Utf8 => downcast_dict_op!(key, StringArray, $array, $op$(, $arg)*),
                DataType::LargeUtf8 => {
                    downcast_dict_op!(key, LargeStringArray, $array, $op$(, $arg)*)
                }
                DataType::Utf8View => {
                    downcast_dict_op!(key, StringViewArray, $array, $op$(, $arg)*)
                }
                DataType::Binary => downcast_dict_op!(key, BinaryArray, $array, $op$(, $arg)*),
                DataType::LargeBinary => {
                    downcast_dict_op!(key, LargeBinaryArray, $array, $op$(, $arg)*)
                }
                DataType::BinaryView => {
                    downcast_dict_op!(key, BinaryViewArray, $array, $op$(, $arg)*)
                }
                DataType::FixedSizeBinary(_) => {
                    downcast_dict_op!(key, FixedSizeBinaryArray, $array, $op$(, $arg)*)
                }
                d => unreachable!("cannot downcast {} dictionary value to byte array", d),
            },
            d => unreachable!("cannot downcast {} to byte array", d),
        }
    };
}

/// A fallback encoder, i.e. non-dictionary, for [`ByteArray`]
struct FallbackEncoder {
    encoder: FallbackEncoderImpl,
    num_values: usize,
    variable_length_bytes: i64,
}

/// The fallback encoder in use
///
/// Note: DeltaBitPackEncoder is boxed as it is rather large
enum FallbackEncoderImpl {
    Plain {
        buffer: Vec<u8>,
    },
    DeltaLength {
        buffer: Vec<u8>,
        lengths: Box<DeltaBitPackEncoder<Int32Type>>,
    },
    Delta {
        buffer: Vec<u8>,
        last_value: Vec<u8>,
        prefix_lengths: Box<DeltaBitPackEncoder<Int32Type>>,
        suffix_lengths: Box<DeltaBitPackEncoder<Int32Type>>,
    },
}

impl FallbackEncoder {
    /// Create the fallback encoder for the given [`WriterProperties`] and the
    /// column settings already resolved from them
    fn new(props: &WriterProperties, column_props: &ResolvedColumnProperties) -> Result<Self> {
        // Set either main encoder or fallback encoder.
        let encoding = column_props
            .encoding
            .unwrap_or_else(|| match props.writer_version() {
                WriterVersion::PARQUET_1_0 => Encoding::PLAIN,
                WriterVersion::PARQUET_2_0 => Encoding::DELTA_BYTE_ARRAY,
            });

        let encoder = match encoding {
            Encoding::PLAIN => FallbackEncoderImpl::Plain { buffer: vec![] },
            Encoding::DELTA_LENGTH_BYTE_ARRAY => FallbackEncoderImpl::DeltaLength {
                buffer: vec![],
                lengths: Box::new(DeltaBitPackEncoder::new()),
            },
            Encoding::DELTA_BYTE_ARRAY => FallbackEncoderImpl::Delta {
                buffer: vec![],
                last_value: vec![],
                prefix_lengths: Box::new(DeltaBitPackEncoder::new()),
                suffix_lengths: Box::new(DeltaBitPackEncoder::new()),
            },
            _ => {
                return Err(general_err!(
                    "unsupported encoding {} for byte array",
                    encoding
                ));
            }
        };

        Ok(Self {
            encoder,
            num_values: 0,
            variable_length_bytes: 0,
        })
    }

    /// Encode `values` to the in-progress page
    fn encode<T>(&mut self, values: T, indices: impl ExactSizeIterator<Item = usize>)
    where
        T: ArrayAccessor + Copy,
        T::Item: AsRef<[u8]>,
    {
        self.num_values += indices.len();
        match &mut self.encoder {
            FallbackEncoderImpl::Plain { buffer } => {
                for idx in indices {
                    let value = values.value(idx);
                    let value = value.as_ref();
                    buffer.extend_from_slice((value.len() as u32).as_bytes());
                    buffer.extend_from_slice(value);
                    self.variable_length_bytes += value.len() as i64;
                }
            }
            FallbackEncoderImpl::DeltaLength { buffer, lengths } => {
                for idx in indices {
                    let value = values.value(idx);
                    let value = value.as_ref();
                    lengths.put(&[value.len() as i32]).unwrap();
                    buffer.extend_from_slice(value);
                    self.variable_length_bytes += value.len() as i64;
                }
            }
            FallbackEncoderImpl::Delta {
                buffer,
                last_value,
                prefix_lengths,
                suffix_lengths,
            } => {
                for idx in indices {
                    let value = values.value(idx);
                    let value = value.as_ref();

                    let prefix_length = common_prefix_length(last_value, value);
                    let suffix_length = value.len() - prefix_length;

                    last_value.clear();
                    last_value.extend_from_slice(value);

                    buffer.extend_from_slice(&value[prefix_length..]);
                    prefix_lengths.put(&[prefix_length as i32]).unwrap();
                    suffix_lengths.put(&[suffix_length as i32]).unwrap();
                    self.variable_length_bytes += value.len() as i64;
                }
            }
        }
    }

    /// Returns an estimate of the data page size in bytes
    ///
    /// This includes:
    /// <already_written_encoded_byte_size> + <estimated_encoded_size_of_unflushed_bytes>
    fn estimated_data_page_size(&self) -> usize {
        match &self.encoder {
            FallbackEncoderImpl::Plain { buffer, .. } => buffer.len(),
            FallbackEncoderImpl::DeltaLength { buffer, lengths } => {
                buffer.len() + lengths.estimated_data_encoded_size()
            }
            FallbackEncoderImpl::Delta {
                buffer,
                prefix_lengths,
                suffix_lengths,
                ..
            } => {
                buffer.len()
                    + prefix_lengths.estimated_data_encoded_size()
                    + suffix_lengths.estimated_data_encoded_size()
            }
        }
    }

    fn flush_data_page(
        &mut self,
        min_value: Option<ByteArray>,
        max_value: Option<ByteArray>,
    ) -> Result<DataPageValues<ByteArray>> {
        let (buf, encoding) = match &mut self.encoder {
            FallbackEncoderImpl::Plain { buffer } => (std::mem::take(buffer), Encoding::PLAIN),
            FallbackEncoderImpl::DeltaLength { buffer, lengths } => {
                let lengths = lengths.flush_buffer()?;

                let mut out = Vec::with_capacity(lengths.len() + buffer.len());
                out.extend_from_slice(&lengths);
                out.extend_from_slice(buffer);
                buffer.clear();
                (out, Encoding::DELTA_LENGTH_BYTE_ARRAY)
            }
            FallbackEncoderImpl::Delta {
                buffer,
                prefix_lengths,
                suffix_lengths,
                last_value,
            } => {
                let prefix_lengths = prefix_lengths.flush_buffer()?;
                let suffix_lengths = suffix_lengths.flush_buffer()?;

                let mut out =
                    Vec::with_capacity(prefix_lengths.len() + suffix_lengths.len() + buffer.len());
                out.extend_from_slice(&prefix_lengths);
                out.extend_from_slice(&suffix_lengths);
                out.extend_from_slice(buffer);
                buffer.clear();
                last_value.clear();
                (out, Encoding::DELTA_BYTE_ARRAY)
            }
        };

        // Capture value of variable_length_bytes and reset for next page
        let variable_length_bytes = Some(self.variable_length_bytes);
        self.variable_length_bytes = 0;

        Ok(DataPageValues {
            buf: buf.into(),
            num_values: std::mem::take(&mut self.num_values),
            encoding,
            min_value,
            max_value,
            nan_count: None,
            variable_length_bytes,
        })
    }
}

/// [`Storage`] for the [`Interner`] used by [`DictEncoder`]
#[derive(Debug, Default)]
struct ByteArrayStorage {
    /// Encoded dictionary data
    page: Vec<u8>,

    values: Vec<std::ops::Range<usize>>,
}

impl Storage for ByteArrayStorage {
    type Key = u64;
    type Value = [u8];

    fn get(&self, idx: Self::Key) -> &Self::Value {
        &self.page[self.values[idx as usize].clone()]
    }

    fn push(&mut self, value: &Self::Value) -> Self::Key {
        let key = self.values.len();

        self.page.reserve(4 + value.len());
        self.page.extend_from_slice((value.len() as u32).as_bytes());

        let start = self.page.len();
        self.page.extend_from_slice(value);
        self.values.push(start..self.page.len());

        key as u64
    }

    fn estimated_memory_size(&self) -> usize {
        self.page.capacity() * std::mem::size_of::<u8>()
            + self.values.capacity() * std::mem::size_of::<std::ops::Range<usize>>()
    }
}

/// A dictionary encoder for byte array data
#[derive(Debug, Default)]
struct DictEncoder {
    interner: Interner<ByteArrayStorage>,
    indices: Vec<u64>,
    variable_length_bytes: i64,
}

impl DictEncoder {
    /// Encode `values` to the in-progress page
    fn encode<T>(&mut self, values: T, indices: impl ExactSizeIterator<Item = usize>)
    where
        T: ArrayAccessor + Copy,
        T::Item: AsRef<[u8]>,
    {
        self.indices.reserve(indices.len());

        for idx in indices {
            let value = values.value(idx);
            let interned = self.interner.intern(value.as_ref());
            self.indices.push(interned);
            self.variable_length_bytes += value.as_ref().len() as i64;
        }
    }

    fn bit_width(&self) -> u8 {
        let length = self.interner.storage().values.len();
        num_required_bits(length.saturating_sub(1) as u64)
    }

    fn estimated_memory_size(&self) -> usize {
        self.interner.estimated_memory_size() + self.indices.capacity() * std::mem::size_of::<u64>()
    }

    fn estimated_data_page_size(&self) -> usize {
        let bit_width = self.bit_width();
        1 + RleEncoder::max_buffer_size(bit_width, self.indices.len())
    }

    fn estimated_dict_page_size(&self) -> usize {
        self.interner.storage().page.len()
    }

    fn flush_dict_page(self) -> DictionaryPage {
        let storage = self.interner.into_inner();

        DictionaryPage {
            buf: storage.page.into(),
            num_values: storage.values.len(),
            is_sorted: false,
        }
    }

    fn flush_data_page(
        &mut self,
        min_value: Option<ByteArray>,
        max_value: Option<ByteArray>,
    ) -> DataPageValues<ByteArray> {
        let num_values = self.indices.len();
        let buffer_len = self.estimated_data_page_size();
        let mut buffer = Vec::with_capacity(buffer_len);
        buffer.push(self.bit_width());

        let mut encoder = RleEncoder::new_from_buf(self.bit_width(), buffer);
        encoder.put_batch(&self.indices);

        self.indices.clear();

        // Capture value of variable_length_bytes and reset for next page
        let variable_length_bytes = Some(self.variable_length_bytes);
        self.variable_length_bytes = 0;

        DataPageValues {
            buf: encoder.consume().into(),
            num_values,
            encoding: Encoding::RLE_DICTIONARY,
            min_value,
            max_value,
            nan_count: None,
            variable_length_bytes,
        }
    }
}

pub struct ByteArrayEncoder {
    fallback: FallbackEncoder,
    dict_encoder: Option<DictEncoder>,
    statistics_enabled: EnabledStatistics,
    min_value: Option<ByteArray>,
    max_value: Option<ByteArray>,
    bloom_filter: Option<Sbbf>,
    bloom_filter_target_fpp: f64,
    geo_stats_accumulator: Option<Box<dyn GeoStatsAccumulator>>,
}

impl ColumnValueEncoder for ByteArrayEncoder {
    type T = ByteArray;
    type Values = dyn Array;
    fn flush_bloom_filter(&mut self) -> Option<Sbbf> {
        let mut sbbf = self.bloom_filter.take()?;
        sbbf.fold_to_target_fpp(self.bloom_filter_target_fpp);
        Some(sbbf)
    }

    fn try_new(
        descr: &ColumnDescPtr,
        props: &WriterProperties,
        column_props: &ResolvedColumnProperties,
    ) -> Result<Self>
    where
        Self: Sized,
    {
        let dictionary = column_props.dictionary_enabled.then(DictEncoder::default);

        let fallback = FallbackEncoder::new(props, column_props)?;

        let (bloom_filter, bloom_filter_target_fpp) = create_bloom_filter(column_props)?;

        let statistics_enabled = column_props.statistics_enabled;

        let geo_stats_accumulator = try_new_geo_stats_accumulator(descr);

        Ok(Self {
            fallback,
            statistics_enabled,
            bloom_filter,
            bloom_filter_target_fpp,
            dict_encoder: dictionary,
            min_value: None,
            max_value: None,
            geo_stats_accumulator,
        })
    }

    fn write(&mut self, _values: &Self::Values, _offset: usize, _len: usize) -> Result<()> {
        unreachable!("should call write_gather instead")
    }

    fn write_gather(&mut self, values: &Self::Values, indices: &[usize]) -> Result<()> {
        downcast_op!(
            values.data_type(),
            values,
            encode,
            indices.iter().copied(),
            self
        );
        Ok(())
    }

    fn count_values_within_byte_budget_gather(
        values: &Self::Values,
        indices: &[usize],
        byte_budget: usize,
    ) -> Option<usize> {
        // `ByteArrayEncoder` only ever writes via `write_gather`, so this
        // is the relevant method.
        //
        // Two-stage walk for the simple offset-buffer byte array types:
        //   1. If indices are contiguous, compute the total payload in
        //      O(1) via a single subtraction on the offsets buffer.
        //      When the total fits the budget — the overwhelmingly
        //      common "small values" case — return immediately.
        //   2. Otherwise, walk per-value byte sizes from the offsets
        //      buffer (still cheap, no slice/UTF-8 construction) and
        //      exit at the first value that pushes the cumulative sum
        //      past the budget. This bounds skewed distributions: an
        //      outlier value is caught wherever it lands in the chunk.
        let count = match values.data_type() {
            DataType::Utf8 => count_within_budget_offsets(
                values.as_any().downcast_ref::<StringArray>().unwrap(),
                indices,
                byte_budget,
            ),
            DataType::LargeUtf8 => count_within_budget_offsets(
                values.as_any().downcast_ref::<LargeStringArray>().unwrap(),
                indices,
                byte_budget,
            ),
            DataType::Binary => count_within_budget_offsets(
                values.as_any().downcast_ref::<BinaryArray>().unwrap(),
                indices,
                byte_budget,
            ),
            DataType::LargeBinary => count_within_budget_offsets(
                values.as_any().downcast_ref::<LargeBinaryArray>().unwrap(),
                indices,
                byte_budget,
            ),
            // View arrays carry each value's length in the low 32 bits of
            // its u128 view word, so lengths are scannable without touching
            // any data buffer — and the common small-value case skips even
            // that scan via an O(1) conservative bound.
            DataType::Utf8View => {
                let array = values.as_any().downcast_ref::<StringViewArray>().unwrap();
                count_within_budget_views(
                    array.views(),
                    indices,
                    byte_budget,
                    max_view_value_len(array.data_buffers()),
                )
            }
            DataType::BinaryView => {
                let array = values.as_any().downcast_ref::<BinaryViewArray>().unwrap();
                count_within_budget_views(
                    array.views(),
                    indices,
                    byte_budget,
                    max_view_value_len(array.data_buffers()),
                )
            }
            // The values in an arrow dictionary are already small and
            // deduplicated, so there is nothing to bound — treat every
            // chunk as fitting and stay on the batched path. (A per-value
            // walk through dict keys on every chunk also measured ~+30-80%
            // slower than `main`.)
            DataType::Dictionary(_, _) => indices.len(),
            // Every byte-array type `ByteArrayEncoder` is constructed for
            // has an explicit arm above. A `Dictionary(value = FixedSizeBinary)`
            // column hits the `Dictionary(_, _)` arm (its `values.data_type()`
            // is `Dictionary`), and a bare `FixedSizeBinary` column is routed
            // to the generic column writer, never this encoder — so no other
            // type can reach here.
            data_type => unreachable!("ByteArrayEncoder cannot be constructed for {data_type:?}"),
        };
        Some(count)
    }

    fn num_values(&self) -> usize {
        match &self.dict_encoder {
            Some(encoder) => encoder.indices.len(),
            None => self.fallback.num_values,
        }
    }

    fn has_dictionary(&self) -> bool {
        self.dict_encoder.is_some()
    }

    fn compresses_against_previous_value(&self) -> bool {
        // While dictionary encoding is active the data page holds RLE
        // indices, which carry no cross-value state; only the DELTA_BYTE_ARRAY
        // fallback shares prefixes with the preceding value.
        self.dict_encoder.is_none()
            && matches!(self.fallback.encoder, FallbackEncoderImpl::Delta { .. })
    }

    fn estimated_memory_size(&self) -> usize {
        let encoder_size = match &self.dict_encoder {
            Some(encoder) => encoder.estimated_memory_size(),
            // For the FallbackEncoder, these unflushed bytes are already encoded.
            // Therefore, the size should be the same as estimated_data_page_size.
            None => self.fallback.estimated_data_page_size(),
        };

        let bloom_filter_size = self
            .bloom_filter
            .as_ref()
            .map(|bf| bf.estimated_memory_size())
            .unwrap_or_default();

        let stats_size = self.min_value.as_ref().map(|v| v.len()).unwrap_or_default()
            + self.max_value.as_ref().map(|v| v.len()).unwrap_or_default();

        encoder_size + bloom_filter_size + stats_size
    }

    fn estimated_dict_page_size(&self) -> Option<usize> {
        Some(self.dict_encoder.as_ref()?.estimated_dict_page_size())
    }

    /// Returns an estimate of the data page size in bytes
    ///
    /// This includes:
    /// <already_written_encoded_byte_size> + <estimated_encoded_size_of_unflushed_bytes>
    fn estimated_data_page_size(&self) -> usize {
        match &self.dict_encoder {
            Some(encoder) => encoder.estimated_data_page_size(),
            None => self.fallback.estimated_data_page_size(),
        }
    }

    fn flush_dict_page(&mut self) -> Result<Option<DictionaryPage>> {
        match self.dict_encoder.take() {
            Some(encoder) => {
                if !encoder.indices.is_empty() {
                    return Err(general_err!(
                        "Must flush data pages before flushing dictionary"
                    ));
                }

                if let Some(bloom_filter) = &mut self.bloom_filter {
                    let storage = encoder.interner.storage();
                    for range in &storage.values {
                        bloom_filter.insert(&storage.page[range.clone()]);
                    }
                }

                Ok(Some(encoder.flush_dict_page()))
            }
            _ => Ok(None),
        }
    }

    fn flush_data_page(&mut self) -> Result<DataPageValues<ByteArray>> {
        let min_value = self.min_value.take();
        let max_value = self.max_value.take();

        match &mut self.dict_encoder {
            Some(encoder) => Ok(encoder.flush_data_page(min_value, max_value)),
            _ => self.fallback.flush_data_page(min_value, max_value),
        }
    }

    fn flush_geospatial_statistics(&mut self) -> Option<Box<GeospatialStatistics>> {
        self.geo_stats_accumulator.as_mut().map(|a| a.finish())?
    }
}

/// Encodes the provided `values` and `indices` to `encoder`
///
/// This is a free function so it can be used with `downcast_op!`
fn encode<T, I>(values: T, indices: I, encoder: &mut ByteArrayEncoder)
where
    T: ArrayAccessor + Copy,
    T::Item: Copy + Ord + AsRef<[u8]>,
    I: ExactSizeIterator<Item = usize> + Clone,
{
    if encoder.statistics_enabled != EnabledStatistics::None {
        if let Some(accumulator) = encoder.geo_stats_accumulator.as_mut() {
            update_geo_stats_accumulator(accumulator.as_mut(), values, indices.clone());
        } else if let Some((min, max)) = compute_min_max(values, indices.clone()) {
            // Compare before copying: `write_gather` runs once per
            // mini-batch, and a byte-budgeted mini-batch of large values can
            // hold a single value, so an unconditional copy here would
            // duplicate every value once for `min` and once for `max`.
            let min = min.as_ref();
            if encoder.min_value.as_ref().is_none_or(|m| m.data() > min) {
                encoder.min_value = Some(min.to_vec().into());
            }

            let max = max.as_ref();
            if encoder.max_value.as_ref().is_none_or(|m| m.data() < max) {
                encoder.max_value = Some(max.to_vec().into());
            }
        }
    }

    // While a dictionary is in use the filter is populated from its distinct values in
    // `flush_dict_page`, so each value is hashed once rather than once per row.
    match &mut encoder.dict_encoder {
        Some(dict_encoder) => dict_encoder.encode(values, indices),
        None => {
            if let Some(bloom_filter) = &mut encoder.bloom_filter {
                for idx in indices.clone() {
                    bloom_filter.insert(values.value(idx).as_ref());
                }
            }
            encoder.fallback.encode(values, indices)
        }
    }
}

/// Upper bound on any single value's byte length in a view array.
fn max_view_value_len(buffers: &[Buffer]) -> usize {
    /// Bytes that fit inline in a u128 view word (the rest is len + prefix).
    const MAX_INLINE_VIEW_LEN: usize = 12;
    // An out-of-line view's data is a contiguous slice of exactly one data
    // buffer, so it cannot exceed the largest buffer; inline views hold at
    // most `MAX_INLINE_VIEW_LEN`. Loose (a value is usually far smaller than
    // a whole buffer) but O(number of buffers) and always sound.
    buffers
        .iter()
        .map(|b| b.len())
        .max()
        .unwrap_or(0)
        .max(MAX_INLINE_VIEW_LEN)
}

/// Number of leading `indices` whose cumulative plain-encoded size fits
/// `byte_budget` (boundary value included), for view arrays (`Utf8View`,
/// `BinaryView`).
fn count_within_budget_views(
    views: &[u128],
    indices: &[usize],
    byte_budget: usize,
    max_value_len: usize,
) -> usize {
    // Each plain-encoded BYTE_ARRAY value carries a 4-byte length prefix, so
    // the budget is compared against `value_len + size_of::<u32>()` — the
    // bytes actually written to the page, not just the payload.
    //
    // Stage 1: O(1) conservative bound. View arrays have no prefix-sum
    // offsets buffer, so the exact span subtraction used by
    // `count_within_budget_offsets` is unavailable; instead bound every
    // value by `max_value_len`. Skips the walk for the common small-value
    // case (what view arrays are built for, and where there is nothing to
    // bound).
    let per_value = max_value_len + std::mem::size_of::<u32>();
    if indices.len().saturating_mul(per_value) <= byte_budget {
        return indices.len();
    }
    // Stage 2: exact per-value scan, reading each length from the low 32
    // bits of its u128 view word (no data-buffer dereference).
    let mut cum: usize = 0;
    for (i, idx) in indices.iter().enumerate() {
        let len = (views[*idx] as u32) as usize;
        cum = cum.saturating_add(len + std::mem::size_of::<u32>());
        if cum > byte_budget {
            return i + 1;
        }
    }
    indices.len()
}

/// Number of leading `indices` whose cumulative plain-encoded size fits
/// `byte_budget` (boundary value included), for offset-buffer byte arrays
/// (`Utf8`/`LargeUtf8`/`Binary`/`LargeBinary`).
///
/// `indices` are assumed sorted ascending — they always are here, since
/// they come from `non_null_indices`, which is built in array order.
fn count_within_budget_offsets<T: ByteArrayType>(
    values: &GenericByteArray<T>,
    indices: &[usize],
    byte_budget: usize,
) -> usize {
    if indices.is_empty() {
        return 0;
    }
    let n = indices.len();
    let first = indices[0];
    let last = indices[n - 1];
    let offsets = values.value_offsets();
    // Each plain-encoded value carries a 4-byte length prefix on the page.
    let prefix_overhead = std::mem::size_of::<u32>();

    // Stage 1: O(1) span upper bound. The span `offsets[last+1] -
    // offsets[first]` covers every array position in `[first, last]`, a
    // superset of `indices` — and the skipped positions in a nullable
    // column are nulls with zero offset delta, so the span still equals the
    // exact payload. If it fits the budget, every value fits. Covers the
    // common small-value case for both non-null and (sparse) nullable
    // columns.
    if last >= first {
        let payload = (offsets[last + 1] - offsets[first]).as_usize();
        if payload + n * prefix_overhead <= byte_budget {
            return n;
        }
    }

    // Stage 2: scan per-index lengths from the offsets buffer.
    let mut cum: usize = 0;
    for (i, idx) in indices.iter().enumerate() {
        let len = (offsets[idx + 1] - offsets[*idx]).as_usize() + prefix_overhead;
        cum = cum.saturating_add(len);
        if cum > byte_budget {
            return i + 1;
        }
    }
    n
}

/// Computes the min and max for the provided array and indices
///
/// This is a free function so it can be used with `downcast_op!`
fn compute_min_max<T>(
    array: T,
    mut valid: impl Iterator<Item = usize>,
) -> Option<(T::Item, T::Item)>
where
    T: ArrayAccessor,
    T::Item: Copy + Ord + AsRef<[u8]>,
{
    let first_idx = valid.next()?;

    let first_val = array.value(first_idx);
    let mut min = first_val;
    let mut max = first_val;
    for idx in valid {
        let val = array.value(idx);
        min = min.min(val);
        max = max.max(val);
    }
    Some((min, max))
}

/// Updates geospatial statistics for the provided array and indices
fn update_geo_stats_accumulator<T>(
    bounder: &mut dyn GeoStatsAccumulator,
    array: T,
    valid: impl Iterator<Item = usize>,
) where
    T: ArrayAccessor,
    T::Item: Copy + Ord + AsRef<[u8]>,
{
    if bounder.is_valid() {
        for idx in valid {
            let val = array.value(idx);
            bounder.update_wkb(val.as_ref());
        }
    }
}