shehabgamin commented on code in PR #19627: URL: https://github.com/apache/datafusion/pull/19627#discussion_r2659261184
########## datafusion/spark/src/function/hash/murmur3_hash.rs: ########## @@ -0,0 +1,474 @@ +// 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 std::any::Any; +use std::sync::Arc; + +use arrow::array::{ + Array, ArrayRef, ArrowNativeTypeOp, AsArray, BinaryArray, BooleanArray, Date32Array, + Date64Array, Decimal128Array, Float32Array, Float64Array, Int8Array, Int16Array, + Int32Array, Int64Array, LargeBinaryArray, LargeStringArray, StringArray, + TimestampMicrosecondArray, TimestampMillisecondArray, TimestampNanosecondArray, + TimestampSecondArray, +}; +use arrow::datatypes::{DataType, TimeUnit}; +use datafusion_common::{Result, ScalarValue, exec_err, internal_err}; +use datafusion_expr::{ + ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility, +}; + +const DEFAULT_SEED: i32 = 42; + +/// Spark-compatible murmur3 hash function. +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hash> +#[derive(Debug, PartialEq, Eq, Hash)] +pub struct SparkMurmur3Hash { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkMurmur3Hash { + fn default() -> Self { + Self::new() + } +} + +impl SparkMurmur3Hash { + pub fn new() -> Self { + Self { + signature: Signature::variadic_any(Volatility::Immutable), + aliases: vec!["hash".to_string()], + } + } +} + +impl ScalarUDFImpl for SparkMurmur3Hash { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "murmur3_hash" + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { + Ok(DataType::Int32) + } + + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { + if args.args.is_empty() { + return exec_err!("murmur3_hash requires at least one argument"); + } + + // Determine number of rows from the first array argument + let num_rows = args + .args + .iter() + .find_map(|arg| match arg { + ColumnarValue::Array(array) => Some(array.len()), + ColumnarValue::Scalar(_) => None, + }) + .unwrap_or(1); + + // Initialize hashes with seed + let mut hashes: Vec<u32> = vec![DEFAULT_SEED as u32; num_rows]; + + // Convert all arguments to arrays + let arrays: Vec<ArrayRef> = args + .args + .iter() + .map(|arg| match arg { + ColumnarValue::Array(array) => Arc::clone(array), + ColumnarValue::Scalar(scalar) => scalar + .to_array_of_size(num_rows) + .expect("Failed to convert scalar to array"), + }) + .collect(); + + // Hash each column + for col in &arrays { + hash_column_murmur3(col, &mut hashes)?; + } + + // Convert to Int32 + let result: Vec<i32> = hashes.into_iter().map(|h| h as i32).collect(); + let result_array = Int32Array::from(result); + + if num_rows == 1 { + Ok(ColumnarValue::Scalar(ScalarValue::Int32(Some( + result_array.value(0), + )))) + } else { + Ok(ColumnarValue::Array(Arc::new(result_array))) + } + } +} + +/// Spark-compatible murmur3 hash algorithm +#[inline] +pub fn spark_compatible_murmur3_hash<T: AsRef<[u8]>>(data: T, seed: u32) -> u32 { + #[inline] + fn mix_k1(mut k1: i32) -> i32 { + k1 = k1.mul_wrapping(0xcc9e2d51u32 as i32); + k1 = k1.rotate_left(15); + k1.mul_wrapping(0x1b873593u32 as i32) + } + + #[inline] + fn mix_h1(mut h1: i32, k1: i32) -> i32 { + h1 ^= k1; + h1 = h1.rotate_left(13); + h1.mul_wrapping(5).add_wrapping(0xe6546b64u32 as i32) + } + + #[inline] + fn fmix(mut h1: i32, len: i32) -> i32 { + h1 ^= len; + h1 ^= (h1 as u32 >> 16) as i32; + h1 = h1.mul_wrapping(0x85ebca6bu32 as i32); + h1 ^= (h1 as u32 >> 13) as i32; + h1 = h1.mul_wrapping(0xc2b2ae35u32 as i32); + h1 ^= (h1 as u32 >> 16) as i32; + h1 + } + + #[inline] + unsafe fn hash_bytes_by_int(data: &[u8], seed: u32) -> i32 { + // SAFETY: caller guarantees data length is aligned to 4 bytes + unsafe { + let mut h1 = seed as i32; + for i in (0..data.len()).step_by(4) { + let ints = data.as_ptr().add(i) as *const i32; + let mut half_word = ints.read_unaligned(); + if cfg!(target_endian = "big") { + half_word = half_word.reverse_bits(); + } + h1 = mix_h1(h1, mix_k1(half_word)); + } + h1 + } + } + + let data = data.as_ref(); + let len = data.len(); + let len_aligned = len - len % 4; + + // SAFETY: all operations are guaranteed to be safe + unsafe { + let mut h1 = if len_aligned > 0 { + hash_bytes_by_int(&data[0..len_aligned], seed) + } else { + seed as i32 + }; + + for i in len_aligned..len { + let half_word = *data.get_unchecked(i) as i8 as i32; + h1 = mix_h1(h1, mix_k1(half_word)); + } + fmix(h1, len as i32) as u32 + } +} + +fn hash_column_murmur3(col: &ArrayRef, hashes: &mut [u32]) -> Result<()> { Review Comment: It looks like support for `DataType::Dictionary` may be missing. In the Sail codebase, we copied the logic from Comet, where the Dictionary type is handled. However, I’m not sure whether Comet’s implementation has changed since we copied it. In Sail, the relevant logic can be found here: - https://github.com/lakehq/sail/blob/540fb8350ab676dfd0c302fafb4176b11fb0ee84/crates/sail-function/src/scalar/hash/spark_murmur3_hash.rs#L68 - https://github.com/lakehq/sail/blob/540fb8350ab676dfd0c302fafb4176b11fb0ee84/crates/sail-function/src/scalar/hash/utils.rs#L12 Based on the attribution comments in those files, the corresponding Comet sources appear to come from the following commit: - https://github.com/apache/datafusion-comet/blob/bfd7054c02950219561428463d3926afaf8edbba/native/spark-expr/src/spark_hash.rs - https://github.com/apache/datafusion-comet/blob/bfd7054c02950219561428463d3926afaf8edbba/native/spark-expr/src/scalar_funcs/hash_expressions.rs#L28-L70 -- This is an automated message from the Apache Git Service. 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