[GitHub] [arrow-datafusion] liukun4515 commented on a change in pull request #1841: Implement bitmap_distinct function using roaring bitmap

[GitBox <gi...@apache.org>]

liukun4515 commented on a change in pull request #1841:
URL: https://github.com/apache/arrow-datafusion/pull/1841#discussion_r810873400



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File path: datafusion/src/physical_plan/expressions/bitmap_distinct.rs
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@@ -0,0 +1,219 @@
+// 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.
+
+//! Defines physical expressions that can evaluated at runtime during query execution
+
+use std::any::Any;
+
+use std::fmt::Debug;
+use std::ops::BitOrAssign;
+use std::sync::Arc;
+
+use arrow::array::{
+    Array, ArrayRef, BinaryArray, Int16Array, Int32Array, Int8Array, UInt16Array,
+    UInt32Array, UInt8Array,
+};
+use arrow::datatypes::{DataType, Field};
+use log::error;
+use roaring::RoaringBitmap;
+
+use crate::error::{DataFusionError, Result};
+use crate::physical_plan::{Accumulator, AggregateExpr, PhysicalExpr};
+use crate::scalar::ScalarValue;
+
+use super::format_state_name;
+
+/// APPROX_DISTINCT aggregate expression
+#[derive(Debug)]
+pub struct BitMapDistinct {
+    name: String,
+    input_data_type: DataType,
+    expr: Arc<dyn PhysicalExpr>,
+}
+
+impl BitMapDistinct {
+    /// Create a new ApproxDistinct aggregate function.
+    pub fn new(
+        expr: Arc<dyn PhysicalExpr>,
+        name: impl Into<String>,
+        input_data_type: DataType,
+    ) -> Self {
+        Self {
+            name: name.into(),
+            input_data_type,
+            expr,
+        }
+    }
+}
+
+impl AggregateExpr for BitMapDistinct {
+    /// Return a reference to Any that can be used for downcasting
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    /// the field of the final result of this aggregation.
+    fn field(&self) -> Result<Field> {
+        Ok(Field::new(&self.name, DataType::UInt64, false))
+    }
+
+    fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
+        let accumulator: Box<dyn Accumulator> = match &self.input_data_type {
+            DataType::UInt8
+            | DataType::UInt16
+            | DataType::UInt32
+            | DataType::Int8
+            | DataType::Int16
+            | DataType::Int32 => Box::new(BitmapDistinctCountAccumulator::try_new()),
+            other => {
+                return Err(DataFusionError::NotImplemented(format!(
+                    "Support for 'bitmap_distinct' for data type {} is not implemented",
+                    other
+                )))
+            }
+        };
+        Ok(accumulator)
+    }
+
+    fn state_fields(&self) -> Result<Vec<Field>> {
+        Ok(vec![Field::new(
+            &format_state_name(&self.name, "bitmap_registers"),
+            DataType::Binary,
+            false,
+        )])
+    }
+
+    fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
+        vec![self.expr.clone()]
+    }
+
+    fn name(&self) -> &str {
+        &self.name
+    }
+}
+
+#[derive(Debug)]
+struct BitmapDistinctCountAccumulator {
+    bitmap: roaring::bitmap::RoaringBitmap,
+}
+
+impl BitmapDistinctCountAccumulator {
+    fn try_new() -> Self {
+        Self {
+            bitmap: RoaringBitmap::new(),
+        }
+    }
+}
+
+impl Accumulator for BitmapDistinctCountAccumulator {
+    //state() can be used by physical nodes to aggregate states together and send them over the network/threads, to combine values.
+    fn state(&self) -> Result<Vec<ScalarValue>> {
+        let mut bytes = vec![];
+        self.bitmap.serialize_into(&mut bytes).unwrap();
+        Ok(vec![ScalarValue::Binary(Some(bytes))])
+    }
+
+    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+        let value = &values[0];
+        if value.is_empty() {
+            return Ok(());
+        }
+        match value.data_type() {
+            DataType::Int8 => {
+                let array = value.as_any().downcast_ref::<Int8Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i) as u32);
+                }
+            }
+            DataType::Int16 => {
+                let array = value.as_any().downcast_ref::<Int16Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i) as u32);
+                }
+            }
+            DataType::Int32 => {
+                let array = value.as_any().downcast_ref::<Int32Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i) as u32);
+                }
+            }
+            DataType::UInt8 => {
+                let array = value.as_any().downcast_ref::<UInt8Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i) as u32);
+                }
+            }
+            DataType::UInt16 => {
+                let array = value.as_any().downcast_ref::<UInt16Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i) as u32);
+                }
+            }
+            DataType::UInt32 => {
+                let array = value.as_any().downcast_ref::<UInt32Array>().unwrap();
+                for i in 0..array.len() {
+                    self.bitmap.insert(array.value(i));
+                }
+            }
+            e => {
+                return Err(DataFusionError::Internal(format!(
+                    "BITMAP_COUNT_DISTINCT is not expected to receive the type {:?}",
+                    e
+                )));
+            }
+        }
+        Ok(())
+    }
+
+    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+        if states.len() != 1 {
+            error!(
+                "expect only 1 element in the states but found {:?}",
+                &states.len()
+            )
+        }
+
+        let binary_array = states[0].as_any().downcast_ref::<BinaryArray>().unwrap();
+
+        for b in binary_array.iter() {
+            let v = b.ok_or_else(|| {
+                DataFusionError::Internal(
+                    "Impossibly got empty binary array from states".into(),
+                )
+            })?;
+            let bitmap = RoaringBitmap::deserialize_from(&v.to_vec()[..]).unwrap();
+            self.bitmap.bitor_assign(bitmap);
+        }
+        Ok(())
+    }
+
+    fn evaluate(&self) -> Result<ScalarValue> {
+        Ok(ScalarValue::from(self.bitmap.len()))
+    }
+}
+
+pub(crate) fn is_bitmap_count_distinct_supported_arg_type(arg_type: &DataType) -> bool {

Review comment:
       Do we need to support U64, I64 or other numeric type?
   @Ted-Jiang 




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