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bloom.go
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bloom.go
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package parquet
import (
"io"
"github.com/parquet-go/parquet-go/bloom"
"github.com/parquet-go/parquet-go/bloom/xxhash"
"github.com/parquet-go/parquet-go/deprecated"
"github.com/parquet-go/parquet-go/encoding"
"github.com/parquet-go/parquet-go/format"
"github.com/parquet-go/parquet-go/internal/unsafecast"
)
// BloomFilter is an interface allowing applications to test whether a key
// exists in a bloom filter.
type BloomFilter interface {
// Implement the io.ReaderAt interface as a mechanism to allow reading the
// raw bits of the filter.
io.ReaderAt
// Returns the size of the bloom filter (in bytes).
Size() int64
// Tests whether the given value is present in the filter.
//
// A non-nil error may be returned if reading the filter failed. This may
// happen if the filter was lazily loaded from a storage medium during the
// call to Check for example. Applications that can guarantee that the
// filter was in memory at the time Check was called can safely ignore the
// error, which would always be nil in this case.
Check(value Value) (bool, error)
}
type bloomFilter struct {
io.SectionReader
hash bloom.Hash
check func(io.ReaderAt, int64, uint64) (bool, error)
}
func (f *bloomFilter) Check(v Value) (bool, error) {
return f.check(&f.SectionReader, f.Size(), v.hash(f.hash))
}
func (v Value) hash(h bloom.Hash) uint64 {
switch v.Kind() {
case Boolean:
return h.Sum64Uint8(v.byte())
case Int32, Float:
return h.Sum64Uint32(v.uint32())
case Int64, Double:
return h.Sum64Uint64(v.uint64())
default: // Int96, ByteArray, FixedLenByteArray, or null
return h.Sum64(v.byteArray())
}
}
func newBloomFilter(file io.ReaderAt, offset int64, header *format.BloomFilterHeader) *bloomFilter {
if header.Algorithm.Block != nil {
if header.Hash.XxHash != nil {
if header.Compression.Uncompressed != nil {
return &bloomFilter{
SectionReader: *io.NewSectionReader(file, offset, int64(header.NumBytes)),
hash: bloom.XXH64{},
check: bloom.CheckSplitBlock,
}
}
}
}
return nil
}
// The BloomFilterColumn interface is a declarative representation of bloom filters
// used when configuring filters on a parquet writer.
type BloomFilterColumn interface {
// Returns the path of the column that the filter applies to.
Path() []string
// Returns the hashing algorithm used when inserting values into a bloom
// filter.
Hash() bloom.Hash
// Returns an encoding which can be used to write columns of values to the
// filter.
Encoding() encoding.Encoding
// Returns the size of the filter needed to encode values in the filter,
// assuming each value will be encoded with the given number of bits.
Size(numValues int64) int
}
// SplitBlockFilter constructs a split block bloom filter object for the column
// at the given path, with the given bitsPerValue.
//
// If you are unsure what number of bitsPerValue to use, 10 is a reasonable
// tradeoff between size and error rate for common datasets.
//
// For more information on the tradeoff between size and error rate, consult
// this website: https://hur.st/bloomfilter/?n=4000&p=0.1&m=&k=1
func SplitBlockFilter(bitsPerValue uint, path ...string) BloomFilterColumn {
return splitBlockFilter{
bitsPerValue: bitsPerValue,
path: path,
}
}
type splitBlockFilter struct {
bitsPerValue uint
path []string
}
func (f splitBlockFilter) Path() []string { return f.path }
func (f splitBlockFilter) Hash() bloom.Hash { return bloom.XXH64{} }
func (f splitBlockFilter) Encoding() encoding.Encoding { return splitBlockEncoding{} }
func (f splitBlockFilter) Size(numValues int64) int {
return bloom.BlockSize * bloom.NumSplitBlocksOf(numValues, f.bitsPerValue)
}
// Creates a header from the given bloom filter.
//
// For now there is only one type of filter supported, but we provide this
// function to suggest a model for extending the implementation if new filters
// are added to the parquet specs.
func bloomFilterHeader(filter BloomFilterColumn) (header format.BloomFilterHeader) {
switch filter.(type) {
case splitBlockFilter:
header.Algorithm.Block = &format.SplitBlockAlgorithm{}
}
switch filter.Hash().(type) {
case bloom.XXH64:
header.Hash.XxHash = &format.XxHash{}
}
header.Compression.Uncompressed = &format.BloomFilterUncompressed{}
return header
}
func searchBloomFilterColumn(filters []BloomFilterColumn, path columnPath) BloomFilterColumn {
for _, f := range filters {
if path.equal(f.Path()) {
return f
}
}
return nil
}
const (
// Size of the stack buffer used to perform bulk operations on bloom filters.
//
// This value was determined as being a good default empirically,
// 128 x uint64 makes a 1KiB buffer which amortizes the cost of calling
// methods of bloom filters while not causing too much stack growth either.
filterEncodeBufferSize = 128
)
type splitBlockEncoding struct {
encoding.NotSupported
}
func (splitBlockEncoding) EncodeBoolean(dst []byte, src []byte) ([]byte, error) {
splitBlockEncodeUint8(bloom.MakeSplitBlockFilter(dst), src)
return dst, nil
}
func (splitBlockEncoding) EncodeInt32(dst []byte, src []int32) ([]byte, error) {
splitBlockEncodeUint32(bloom.MakeSplitBlockFilter(dst), unsafecast.Slice[uint32](src))
return dst, nil
}
func (splitBlockEncoding) EncodeInt64(dst []byte, src []int64) ([]byte, error) {
splitBlockEncodeUint64(bloom.MakeSplitBlockFilter(dst), unsafecast.Slice[uint64](src))
return dst, nil
}
func (e splitBlockEncoding) EncodeInt96(dst []byte, src []deprecated.Int96) ([]byte, error) {
splitBlockEncodeFixedLenByteArray(bloom.MakeSplitBlockFilter(dst), unsafecast.Slice[byte](src), 12)
return dst, nil
}
func (splitBlockEncoding) EncodeFloat(dst []byte, src []float32) ([]byte, error) {
splitBlockEncodeUint32(bloom.MakeSplitBlockFilter(dst), unsafecast.Slice[uint32](src))
return dst, nil
}
func (splitBlockEncoding) EncodeDouble(dst []byte, src []float64) ([]byte, error) {
splitBlockEncodeUint64(bloom.MakeSplitBlockFilter(dst), unsafecast.Slice[uint64](src))
return dst, nil
}
func (splitBlockEncoding) EncodeByteArray(dst []byte, src []byte, offsets []uint32) ([]byte, error) {
filter := bloom.MakeSplitBlockFilter(dst)
buffer := make([]uint64, 0, filterEncodeBufferSize)
baseOffset := offsets[0]
for _, endOffset := range offsets[1:] {
value := src[baseOffset:endOffset:endOffset]
baseOffset = endOffset
if len(buffer) == cap(buffer) {
filter.InsertBulk(buffer)
buffer = buffer[:0]
}
buffer = append(buffer, xxhash.Sum64(value))
}
filter.InsertBulk(buffer)
return dst, nil
}
func (splitBlockEncoding) EncodeFixedLenByteArray(dst []byte, src []byte, size int) ([]byte, error) {
filter := bloom.MakeSplitBlockFilter(dst)
if size == 16 {
splitBlockEncodeUint128(filter, unsafecast.Slice[[16]byte](src))
} else {
splitBlockEncodeFixedLenByteArray(filter, src, size)
}
return dst, nil
}
func splitBlockEncodeFixedLenByteArray(filter bloom.SplitBlockFilter, data []byte, size int) {
buffer := make([]uint64, 0, filterEncodeBufferSize)
for i, j := 0, size; j <= len(data); {
if len(buffer) == cap(buffer) {
filter.InsertBulk(buffer)
buffer = buffer[:0]
}
buffer = append(buffer, xxhash.Sum64(data[i:j]))
i += size
j += size
}
filter.InsertBulk(buffer)
}
func splitBlockEncodeUint8(filter bloom.SplitBlockFilter, values []uint8) {
buffer := make([]uint64, filterEncodeBufferSize)
for i := 0; i < len(values); {
n := xxhash.MultiSum64Uint8(buffer, values[i:])
filter.InsertBulk(buffer[:n])
i += n
}
}
func splitBlockEncodeUint32(filter bloom.SplitBlockFilter, values []uint32) {
buffer := make([]uint64, filterEncodeBufferSize)
for i := 0; i < len(values); {
n := xxhash.MultiSum64Uint32(buffer, values[i:])
filter.InsertBulk(buffer[:n])
i += n
}
}
func splitBlockEncodeUint64(filter bloom.SplitBlockFilter, values []uint64) {
buffer := make([]uint64, filterEncodeBufferSize)
for i := 0; i < len(values); {
n := xxhash.MultiSum64Uint64(buffer, values[i:])
filter.InsertBulk(buffer[:n])
i += n
}
}
func splitBlockEncodeUint128(filter bloom.SplitBlockFilter, values [][16]byte) {
buffer := make([]uint64, filterEncodeBufferSize)
for i := 0; i < len(values); {
n := xxhash.MultiSum64Uint128(buffer, values[i:])
filter.InsertBulk(buffer[:n])
i += n
}
}