parquet/bloom_filter/mod.rs
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// 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.
//! Bloom filter implementation specific to Parquet, as described
//! in the [spec][parquet-bf-spec].
//!
//! # Bloom Filter Size
//!
//! Parquet uses the [Split Block Bloom Filter][sbbf-paper] (SBBF) as its bloom filter
//! implementation. For each column upon which bloom filters are enabled, the offset and length of an SBBF
//! is stored in the metadata for each row group in the parquet file. The size of each filter is
//! initialized using a calculation based on the desired number of distinct values (NDV) and false
//! positive probability (FPP). The FPP for a SBBF can be approximated as<sup>[1][bf-formulae]</sup>:
//!
//! ```text
//! f = (1 - e^(-k * n / m))^k
//! ```
//!
//! Where, `f` is the FPP, `k` the number of hash functions, `n` the NDV, and `m` the total number
//! of bits in the bloom filter. This can be re-arranged to determine the total number of bits
//! required to achieve a given FPP and NDV:
//!
//! ```text
//! m = -k * n / ln(1 - f^(1/k))
//! ```
//!
//! SBBFs use eight hash functions to cleanly fit in SIMD lanes<sup>[2][sbbf-paper]</sup>, therefore
//! `k` is set to 8. The SBBF will spread those `m` bits accross a set of `b` blocks that
//! are each 256 bits, i.e., 32 bytes, in size. The number of blocks is chosen as:
//!
//! ```text
//! b = NP2(m/8) / 32
//! ```
//!
//! Where, `NP2` denotes *the next power of two*, and `m` is divided by 8 to be represented as bytes.
//!
//! Here is a table of calculated sizes for various FPP and NDV:
//!
//! | NDV | FPP | b | Size (KB) |
//! |-----------|-----------|---------|-----------|
//! | 10,000 | 0.1 | 256 | 8 |
//! | 10,000 | 0.01 | 512 | 16 |
//! | 10,000 | 0.001 | 1,024 | 32 |
//! | 10,000 | 0.0001 | 1,024 | 32 |
//! | 100,000 | 0.1 | 4,096 | 128 |
//! | 100,000 | 0.01 | 4,096 | 128 |
//! | 100,000 | 0.001 | 8,192 | 256 |
//! | 100,000 | 0.0001 | 16,384 | 512 |
//! | 100,000 | 0.00001 | 16,384 | 512 |
//! | 1,000,000 | 0.1 | 32,768 | 1,024 |
//! | 1,000,000 | 0.01 | 65,536 | 2,048 |
//! | 1,000,000 | 0.001 | 65,536 | 2,048 |
//! | 1,000,000 | 0.0001 | 131,072 | 4,096 |
//! | 1,000,000 | 0.00001 | 131,072 | 4,096 |
//! | 1,000,000 | 0.000001 | 262,144 | 8,192 |
//!
//! [parquet-bf-spec]: https://github.com/apache/parquet-format/blob/master/BloomFilter.md
//! [sbbf-paper]: https://arxiv.org/pdf/2101.01719
//! [bf-formulae]: http://tfk.mit.edu/pdf/bloom.pdf
use crate::data_type::AsBytes;
use crate::errors::ParquetError;
use crate::file::metadata::ColumnChunkMetaData;
use crate::file::reader::ChunkReader;
use crate::format::{
BloomFilterAlgorithm, BloomFilterCompression, BloomFilterHash, BloomFilterHeader,
SplitBlockAlgorithm, Uncompressed, XxHash,
};
use crate::thrift::{TCompactSliceInputProtocol, TSerializable};
use bytes::Bytes;
use std::hash::Hasher;
use std::io::Write;
use std::sync::Arc;
use thrift::protocol::{TCompactOutputProtocol, TOutputProtocol};
use twox_hash::XxHash64;
/// Salt as defined in the [spec](https://github.com/apache/parquet-format/blob/master/BloomFilter.md#technical-approach).
const SALT: [u32; 8] = [
0x47b6137b_u32,
0x44974d91_u32,
0x8824ad5b_u32,
0xa2b7289d_u32,
0x705495c7_u32,
0x2df1424b_u32,
0x9efc4947_u32,
0x5c6bfb31_u32,
];
/// Each block is 256 bits, broken up into eight contiguous "words", each consisting of 32 bits.
/// Each word is thought of as an array of bits; each bit is either "set" or "not set".
#[derive(Debug, Copy, Clone)]
struct Block([u32; 8]);
impl Block {
const ZERO: Block = Block([0; 8]);
/// takes as its argument a single unsigned 32-bit integer and returns a block in which each
/// word has exactly one bit set.
fn mask(x: u32) -> Self {
let mut result = [0_u32; 8];
for i in 0..8 {
// wrapping instead of checking for overflow
let y = x.wrapping_mul(SALT[i]);
let y = y >> 27;
result[i] = 1 << y;
}
Self(result)
}
#[inline]
#[cfg(target_endian = "little")]
fn to_le_bytes(self) -> [u8; 32] {
self.to_ne_bytes()
}
#[inline]
#[cfg(not(target_endian = "little"))]
fn to_le_bytes(self) -> [u8; 32] {
self.swap_bytes().to_ne_bytes()
}
#[inline]
fn to_ne_bytes(self) -> [u8; 32] {
// SAFETY: [u32; 8] and [u8; 32] have the same size and neither has invalid bit patterns.
unsafe { std::mem::transmute(self.0) }
}
#[inline]
#[cfg(not(target_endian = "little"))]
fn swap_bytes(mut self) -> Self {
self.0.iter_mut().for_each(|x| *x = x.swap_bytes());
self
}
/// setting every bit in the block that was also set in the result from mask
fn insert(&mut self, hash: u32) {
let mask = Self::mask(hash);
for i in 0..8 {
self[i] |= mask[i];
}
}
/// returns true when every bit that is set in the result of mask is also set in the block.
fn check(&self, hash: u32) -> bool {
let mask = Self::mask(hash);
for i in 0..8 {
if self[i] & mask[i] == 0 {
return false;
}
}
true
}
}
impl std::ops::Index<usize> for Block {
type Output = u32;
#[inline]
fn index(&self, index: usize) -> &Self::Output {
self.0.index(index)
}
}
impl std::ops::IndexMut<usize> for Block {
#[inline]
fn index_mut(&mut self, index: usize) -> &mut Self::Output {
self.0.index_mut(index)
}
}
/// A split block Bloom filter.
///
/// The creation of this structure is based on the [`crate::file::properties::BloomFilterProperties`]
/// struct set via [`crate::file::properties::WriterProperties`] and is thus hidden by default.
#[derive(Debug, Clone)]
pub struct Sbbf(Vec<Block>);
pub(crate) const SBBF_HEADER_SIZE_ESTIMATE: usize = 20;
/// given an initial offset, and a byte buffer, try to read out a bloom filter header and return
/// both the header and the offset after it (for bitset).
pub(crate) fn chunk_read_bloom_filter_header_and_offset(
offset: u64,
buffer: Bytes,
) -> Result<(BloomFilterHeader, u64), ParquetError> {
let (header, length) = read_bloom_filter_header_and_length(buffer)?;
Ok((header, offset + length))
}
/// given a [Bytes] buffer, try to read out a bloom filter header and return both the header and
/// length of the header.
#[inline]
pub(crate) fn read_bloom_filter_header_and_length(
buffer: Bytes,
) -> Result<(BloomFilterHeader, u64), ParquetError> {
let total_length = buffer.len();
let mut prot = TCompactSliceInputProtocol::new(buffer.as_ref());
let header = BloomFilterHeader::read_from_in_protocol(&mut prot)
.map_err(|e| ParquetError::General(format!("Could not read bloom filter header: {e}")))?;
Ok((header, (total_length - prot.as_slice().len()) as u64))
}
pub(crate) const BITSET_MIN_LENGTH: usize = 32;
pub(crate) const BITSET_MAX_LENGTH: usize = 128 * 1024 * 1024;
#[inline]
fn optimal_num_of_bytes(num_bytes: usize) -> usize {
let num_bytes = num_bytes.min(BITSET_MAX_LENGTH);
let num_bytes = num_bytes.max(BITSET_MIN_LENGTH);
num_bytes.next_power_of_two()
}
// see http://algo2.iti.kit.edu/documents/cacheefficientbloomfilters-jea.pdf
// given fpp = (1 - e^(-k * n / m)) ^ k
// we have m = - k * n / ln(1 - fpp ^ (1 / k))
// where k = number of hash functions, m = number of bits, n = number of distinct values
#[inline]
fn num_of_bits_from_ndv_fpp(ndv: u64, fpp: f64) -> usize {
let num_bits = -8.0 * ndv as f64 / (1.0 - fpp.powf(1.0 / 8.0)).ln();
num_bits as usize
}
impl Sbbf {
/// Create a new [Sbbf] with given number of distinct values and false positive probability.
/// Will return an error if `fpp` is greater than or equal to 1.0 or less than 0.0.
pub(crate) fn new_with_ndv_fpp(ndv: u64, fpp: f64) -> Result<Self, ParquetError> {
if !(0.0..1.0).contains(&fpp) {
return Err(ParquetError::General(format!(
"False positive probability must be between 0.0 and 1.0, got {fpp}"
)));
}
let num_bits = num_of_bits_from_ndv_fpp(ndv, fpp);
Ok(Self::new_with_num_of_bytes(num_bits / 8))
}
/// Create a new [Sbbf] with given number of bytes, the exact number of bytes will be adjusted
/// to the next power of two bounded by [BITSET_MIN_LENGTH] and [BITSET_MAX_LENGTH].
pub(crate) fn new_with_num_of_bytes(num_bytes: usize) -> Self {
let num_bytes = optimal_num_of_bytes(num_bytes);
let bitset = vec![0_u8; num_bytes];
Self::new(&bitset)
}
pub(crate) fn new(bitset: &[u8]) -> Self {
let data = bitset
.chunks_exact(4 * 8)
.map(|chunk| {
let mut block = Block::ZERO;
for (i, word) in chunk.chunks_exact(4).enumerate() {
block[i] = u32::from_le_bytes(word.try_into().unwrap());
}
block
})
.collect::<Vec<Block>>();
Self(data)
}
/// Write the bloom filter data (header and then bitset) to the output. This doesn't
/// flush the writer in order to boost performance of bulk writing all blocks. Caller
/// must remember to flush the writer.
pub(crate) fn write<W: Write>(&self, mut writer: W) -> Result<(), ParquetError> {
let mut protocol = TCompactOutputProtocol::new(&mut writer);
let header = self.header();
header.write_to_out_protocol(&mut protocol).map_err(|e| {
ParquetError::General(format!("Could not write bloom filter header: {e}"))
})?;
protocol.flush()?;
self.write_bitset(&mut writer)?;
Ok(())
}
/// Write the bitset in serialized form to the writer.
fn write_bitset<W: Write>(&self, mut writer: W) -> Result<(), ParquetError> {
for block in &self.0 {
writer
.write_all(block.to_le_bytes().as_slice())
.map_err(|e| {
ParquetError::General(format!("Could not write bloom filter bit set: {e}"))
})?;
}
Ok(())
}
/// Create and populate [`BloomFilterHeader`] from this bitset for writing to serialized form
fn header(&self) -> BloomFilterHeader {
BloomFilterHeader {
// 8 i32 per block, 4 bytes per i32
num_bytes: self.0.len() as i32 * 4 * 8,
algorithm: BloomFilterAlgorithm::BLOCK(SplitBlockAlgorithm {}),
hash: BloomFilterHash::XXHASH(XxHash {}),
compression: BloomFilterCompression::UNCOMPRESSED(Uncompressed {}),
}
}
/// Read a new bloom filter from the given offset in the given reader.
pub(crate) fn read_from_column_chunk<R: ChunkReader>(
column_metadata: &ColumnChunkMetaData,
reader: Arc<R>,
) -> Result<Option<Self>, ParquetError> {
let offset: u64 = if let Some(offset) = column_metadata.bloom_filter_offset() {
offset
.try_into()
.map_err(|_| ParquetError::General("Bloom filter offset is invalid".to_string()))?
} else {
return Ok(None);
};
let buffer = match column_metadata.bloom_filter_length() {
Some(length) => reader.get_bytes(offset, length as usize),
None => reader.get_bytes(offset, SBBF_HEADER_SIZE_ESTIMATE),
}?;
let (header, bitset_offset) =
chunk_read_bloom_filter_header_and_offset(offset, buffer.clone())?;
match header.algorithm {
BloomFilterAlgorithm::BLOCK(_) => {
// this match exists to future proof the singleton algorithm enum
}
}
match header.compression {
BloomFilterCompression::UNCOMPRESSED(_) => {
// this match exists to future proof the singleton compression enum
}
}
match header.hash {
BloomFilterHash::XXHASH(_) => {
// this match exists to future proof the singleton hash enum
}
}
let bitset = match column_metadata.bloom_filter_length() {
Some(_) => buffer.slice((bitset_offset - offset) as usize..),
None => {
let bitset_length: usize = header.num_bytes.try_into().map_err(|_| {
ParquetError::General("Bloom filter length is invalid".to_string())
})?;
reader.get_bytes(bitset_offset, bitset_length)?
}
};
Ok(Some(Self::new(&bitset)))
}
#[inline]
fn hash_to_block_index(&self, hash: u64) -> usize {
// unchecked_mul is unstable, but in reality this is safe, we'd just use saturating mul
// but it will not saturate
(((hash >> 32).saturating_mul(self.0.len() as u64)) >> 32) as usize
}
/// Insert an [AsBytes] value into the filter
pub fn insert<T: AsBytes + ?Sized>(&mut self, value: &T) {
self.insert_hash(hash_as_bytes(value));
}
/// Insert a hash into the filter
fn insert_hash(&mut self, hash: u64) {
let block_index = self.hash_to_block_index(hash);
self.0[block_index].insert(hash as u32)
}
/// Check if an [AsBytes] value is probably present or definitely absent in the filter
pub fn check<T: AsBytes>(&self, value: &T) -> bool {
self.check_hash(hash_as_bytes(value))
}
/// Check if a hash is in the filter. May return
/// true for values that was never inserted ("false positive")
/// but will always return false if a hash has not been inserted.
fn check_hash(&self, hash: u64) -> bool {
let block_index = self.hash_to_block_index(hash);
self.0[block_index].check(hash as u32)
}
/// Return the total in memory size of this bloom filter in bytes
pub(crate) fn estimated_memory_size(&self) -> usize {
self.0.capacity() * std::mem::size_of::<Block>()
}
}
// per spec we use xxHash with seed=0
const SEED: u64 = 0;
#[inline]
fn hash_as_bytes<A: AsBytes + ?Sized>(value: &A) -> u64 {
let mut hasher = XxHash64::with_seed(SEED);
hasher.write(value.as_bytes());
hasher.finish()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_hash_bytes() {
assert_eq!(hash_as_bytes(""), 17241709254077376921);
}
#[test]
fn test_mask_set_quick_check() {
for i in 0..1_000_000 {
let result = Block::mask(i);
assert!(result.0.iter().all(|&x| x.is_power_of_two()));
}
}
#[test]
fn test_block_insert_and_check() {
for i in 0..1_000_000 {
let mut block = Block::ZERO;
block.insert(i);
assert!(block.check(i));
}
}
#[test]
fn test_sbbf_insert_and_check() {
let mut sbbf = Sbbf(vec![Block::ZERO; 1_000]);
for i in 0..1_000_000 {
sbbf.insert(&i);
assert!(sbbf.check(&i));
}
}
#[test]
fn test_with_fixture() {
// bloom filter produced by parquet-mr/spark for a column of i64 f"a{i}" for i in 0..10
let bitset: &[u8] = &[
200, 1, 80, 20, 64, 68, 8, 109, 6, 37, 4, 67, 144, 80, 96, 32, 8, 132, 43, 33, 0, 5,
99, 65, 2, 0, 224, 44, 64, 78, 96, 4,
];
let sbbf = Sbbf::new(bitset);
for a in 0..10i64 {
let value = format!("a{a}");
assert!(sbbf.check(&value.as_str()));
}
}
/// test the assumption that bloom filter header size should not exceed SBBF_HEADER_SIZE_ESTIMATE
/// essentially we are testing that the struct is packed with 4 i32 fields, each can be 1-5 bytes
/// so altogether it'll be 20 bytes at most.
#[test]
fn test_bloom_filter_header_size_assumption() {
let buffer: &[u8; 16] = &[21, 64, 28, 28, 0, 0, 28, 28, 0, 0, 28, 28, 0, 0, 0, 99];
let (
BloomFilterHeader {
algorithm,
compression,
hash,
num_bytes,
},
read_length,
) = read_bloom_filter_header_and_length(Bytes::copy_from_slice(buffer)).unwrap();
assert_eq!(read_length, 15);
assert_eq!(
algorithm,
BloomFilterAlgorithm::BLOCK(SplitBlockAlgorithm {})
);
assert_eq!(
compression,
BloomFilterCompression::UNCOMPRESSED(Uncompressed {})
);
assert_eq!(hash, BloomFilterHash::XXHASH(XxHash {}));
assert_eq!(num_bytes, 32_i32);
assert_eq!(20, SBBF_HEADER_SIZE_ESTIMATE);
}
#[test]
fn test_optimal_num_of_bytes() {
for (input, expected) in &[
(0, 32),
(9, 32),
(31, 32),
(32, 32),
(33, 64),
(99, 128),
(1024, 1024),
(999_000_000, 128 * 1024 * 1024),
] {
assert_eq!(*expected, optimal_num_of_bytes(*input));
}
}
#[test]
fn test_num_of_bits_from_ndv_fpp() {
for (fpp, ndv, num_bits) in &[
(0.1, 10, 57),
(0.01, 10, 96),
(0.001, 10, 146),
(0.1, 100, 577),
(0.01, 100, 968),
(0.001, 100, 1460),
(0.1, 1000, 5772),
(0.01, 1000, 9681),
(0.001, 1000, 14607),
(0.1, 10000, 57725),
(0.01, 10000, 96815),
(0.001, 10000, 146076),
(0.1, 100000, 577254),
(0.01, 100000, 968152),
(0.001, 100000, 1460769),
(0.1, 1000000, 5772541),
(0.01, 1000000, 9681526),
(0.001, 1000000, 14607697),
(1e-50, 1_000_000_000_000, 14226231280773240832),
] {
assert_eq!(*num_bits, num_of_bits_from_ndv_fpp(*ndv, *fpp) as u64);
}
}
}