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[GitHub] [arrow-datafusion] realno opened a new pull request #1561: add correlation function
realno opened a new pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561
# Which issue does this PR close?
This PR add the `corr` function which is part of https://github.com/apache/arrow-datafusion/issues/1486
# Rationale for this change
Add correlation function to DataFusion.
# What changes are included in this PR?
New function `corr(col1, co2)` is added.
# Are there any user-facing changes?
New function `corr(col1, co2)` is added.
No breaking change.
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[GitHub] [arrow-datafusion] realno commented on a change in pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
realno commented on a change in pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#discussion_r785395255
##########
File path: datafusion/src/physical_plan/expressions/correlation.rs
##########
@@ -0,0 +1,546 @@
+// 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::sync::Arc;
+
+use crate::error::{DataFusionError, Result};
+use crate::physical_plan::{
+ expressions::{covariance::CovarianceAccumulator, stddev::StddevAccumulator},
+ Accumulator, AggregateExpr, PhysicalExpr,
+};
+use crate::scalar::ScalarValue;
+use arrow::{array::ArrayRef, datatypes::DataType, datatypes::Field};
+
+use super::{format_state_name, StatsType};
+
+/// CORR aggregate expression
+#[derive(Debug)]
+pub struct Correlation {
+ name: String,
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+}
+
+/// function return type of correlation
+pub(crate) fn correlation_return_type(arg_type: &DataType) -> Result<DataType> {
+ match arg_type {
+ DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Float32
+ | DataType::Float64 => Ok(DataType::Float64),
+ other => Err(DataFusionError::Plan(format!(
+ "CORR does not support {:?}",
+ other
+ ))),
+ }
+}
+
+pub(crate) fn is_correlation_support_arg_type(arg_type: &DataType) -> bool {
+ matches!(
+ arg_type,
+ DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::Float32
+ | DataType::Float64
+ )
+}
+
+impl Correlation {
+ /// Create a new COVAR_POP aggregate function
+ pub fn new(
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+ name: impl Into<String>,
+ data_type: DataType,
+ ) -> Self {
+ // the result of correlation just support FLOAT64 data type.
+ assert!(matches!(data_type, DataType::Float64));
+ Self {
+ name: name.into(),
+ expr1,
+ expr2,
+ }
+ }
+}
+
+impl AggregateExpr for Correlation {
+ /// Return a reference to Any that can be used for downcasting
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn field(&self) -> Result<Field> {
+ Ok(Field::new(&self.name, DataType::Float64, true))
+ }
+
+ fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
+ Ok(Box::new(CorrelationAccumulator::try_new()?))
+ }
+
+ fn state_fields(&self) -> Result<Vec<Field>> {
+ Ok(vec![
+ Field::new(
+ &format_state_name(&self.name, "count"),
+ DataType::UInt64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "algo_const"),
+ DataType::Float64,
+ true,
+ ),
+ ])
+ }
+
+ fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
+ vec![self.expr1.clone(), self.expr2.clone()]
+ }
+
+ fn name(&self) -> &str {
+ &self.name
+ }
+}
+
+/// An accumulator to compute correlation
+#[derive(Debug)]
+pub struct CorrelationAccumulator {
+ covar: CovarianceAccumulator,
+ stddev1: StddevAccumulator,
+ stddev2: StddevAccumulator,
+}
+
+impl CorrelationAccumulator {
+ /// Creates a new `CorrelationAccumulator`
+ pub fn try_new() -> Result<Self> {
+ Ok(Self {
+ covar: CovarianceAccumulator::try_new(StatsType::Population)?,
+ stddev1: StddevAccumulator::try_new(StatsType::Population)?,
+ stddev2: StddevAccumulator::try_new(StatsType::Population)?,
+ })
+ }
+}
+
+impl Accumulator for CorrelationAccumulator {
+ fn state(&self) -> Result<Vec<ScalarValue>> {
+ Ok(vec![
+ ScalarValue::from(self.covar.get_count()),
+ ScalarValue::from(self.covar.get_mean1()),
+ ScalarValue::from(self.stddev1.get_m2()),
+ ScalarValue::from(self.covar.get_mean2()),
+ ScalarValue::from(self.stddev2.get_m2()),
+ ScalarValue::from(self.covar.get_algo_const()),
+ ])
+ }
+
+ fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+ self.covar.update_batch(values)?;
+ self.stddev1.update_batch(&[values[0].clone()])?;
+ self.stddev2.update_batch(&[values[1].clone()])?;
+ Ok(())
+ }
+
+ fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+ let states_c = [
+ states[0].clone(),
+ states[1].clone(),
+ states[3].clone(),
+ states[5].clone(),
+ ];
+ let states_s1 = [states[0].clone(), states[1].clone(), states[2].clone()];
+ let states_s2 = [states[0].clone(), states[3].clone(), states[4].clone()];
+
+ self.covar.merge_batch(&states_c)?;
+ self.stddev1.merge_batch(&states_s1)?;
+ self.stddev2.merge_batch(&states_s2)?;
+ Ok(())
+ }
+
+ fn update(&mut self, _values: &[ScalarValue]) -> Result<()> {
+ unimplemented!("update_batch is implemented instead");
+ }
+
+ fn merge(&mut self, _states: &[ScalarValue]) -> Result<()> {
+ unimplemented!("merge_batch is implemented instead");
+ }
+
+ fn evaluate(&self) -> Result<ScalarValue> {
+ let covar = self.covar.evaluate()?;
+ let stddev1 = self.stddev1.evaluate()?;
+ let stddev2 = self.stddev2.evaluate()?;
+
+ if let ScalarValue::Float64(Some(c)) = covar {
+ if let ScalarValue::Float64(Some(s1)) = stddev1 {
+ if let ScalarValue::Float64(Some(s2)) = stddev2 {
+ return Ok(ScalarValue::Float64(Some(c / s1 / s2)));
Review comment:
They may be 0, pushed a fix. Thanks!
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[GitHub] [arrow-datafusion] liukun4515 edited a comment on pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
liukun4515 edited a comment on pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#issuecomment-1012834188
why not support `covar_pop` and `covar_samp` together?
reference https://www.postgresql.org/docs/14/functions-aggregate.html
@realno
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[GitHub] [arrow-datafusion] realno commented on a change in pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
realno commented on a change in pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#discussion_r785395255
##########
File path: datafusion/src/physical_plan/expressions/correlation.rs
##########
@@ -0,0 +1,546 @@
+// 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::sync::Arc;
+
+use crate::error::{DataFusionError, Result};
+use crate::physical_plan::{
+ expressions::{covariance::CovarianceAccumulator, stddev::StddevAccumulator},
+ Accumulator, AggregateExpr, PhysicalExpr,
+};
+use crate::scalar::ScalarValue;
+use arrow::{array::ArrayRef, datatypes::DataType, datatypes::Field};
+
+use super::{format_state_name, StatsType};
+
+/// CORR aggregate expression
+#[derive(Debug)]
+pub struct Correlation {
+ name: String,
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+}
+
+/// function return type of correlation
+pub(crate) fn correlation_return_type(arg_type: &DataType) -> Result<DataType> {
+ match arg_type {
+ DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Float32
+ | DataType::Float64 => Ok(DataType::Float64),
+ other => Err(DataFusionError::Plan(format!(
+ "CORR does not support {:?}",
+ other
+ ))),
+ }
+}
+
+pub(crate) fn is_correlation_support_arg_type(arg_type: &DataType) -> bool {
+ matches!(
+ arg_type,
+ DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::Float32
+ | DataType::Float64
+ )
+}
+
+impl Correlation {
+ /// Create a new COVAR_POP aggregate function
+ pub fn new(
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+ name: impl Into<String>,
+ data_type: DataType,
+ ) -> Self {
+ // the result of correlation just support FLOAT64 data type.
+ assert!(matches!(data_type, DataType::Float64));
+ Self {
+ name: name.into(),
+ expr1,
+ expr2,
+ }
+ }
+}
+
+impl AggregateExpr for Correlation {
+ /// Return a reference to Any that can be used for downcasting
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn field(&self) -> Result<Field> {
+ Ok(Field::new(&self.name, DataType::Float64, true))
+ }
+
+ fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
+ Ok(Box::new(CorrelationAccumulator::try_new()?))
+ }
+
+ fn state_fields(&self) -> Result<Vec<Field>> {
+ Ok(vec![
+ Field::new(
+ &format_state_name(&self.name, "count"),
+ DataType::UInt64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "algo_const"),
+ DataType::Float64,
+ true,
+ ),
+ ])
+ }
+
+ fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
+ vec![self.expr1.clone(), self.expr2.clone()]
+ }
+
+ fn name(&self) -> &str {
+ &self.name
+ }
+}
+
+/// An accumulator to compute correlation
+#[derive(Debug)]
+pub struct CorrelationAccumulator {
+ covar: CovarianceAccumulator,
+ stddev1: StddevAccumulator,
+ stddev2: StddevAccumulator,
+}
+
+impl CorrelationAccumulator {
+ /// Creates a new `CorrelationAccumulator`
+ pub fn try_new() -> Result<Self> {
+ Ok(Self {
+ covar: CovarianceAccumulator::try_new(StatsType::Population)?,
+ stddev1: StddevAccumulator::try_new(StatsType::Population)?,
+ stddev2: StddevAccumulator::try_new(StatsType::Population)?,
+ })
+ }
+}
+
+impl Accumulator for CorrelationAccumulator {
+ fn state(&self) -> Result<Vec<ScalarValue>> {
+ Ok(vec![
+ ScalarValue::from(self.covar.get_count()),
+ ScalarValue::from(self.covar.get_mean1()),
+ ScalarValue::from(self.stddev1.get_m2()),
+ ScalarValue::from(self.covar.get_mean2()),
+ ScalarValue::from(self.stddev2.get_m2()),
+ ScalarValue::from(self.covar.get_algo_const()),
+ ])
+ }
+
+ fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+ self.covar.update_batch(values)?;
+ self.stddev1.update_batch(&[values[0].clone()])?;
+ self.stddev2.update_batch(&[values[1].clone()])?;
+ Ok(())
+ }
+
+ fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+ let states_c = [
+ states[0].clone(),
+ states[1].clone(),
+ states[3].clone(),
+ states[5].clone(),
+ ];
+ let states_s1 = [states[0].clone(), states[1].clone(), states[2].clone()];
+ let states_s2 = [states[0].clone(), states[3].clone(), states[4].clone()];
+
+ self.covar.merge_batch(&states_c)?;
+ self.stddev1.merge_batch(&states_s1)?;
+ self.stddev2.merge_batch(&states_s2)?;
+ Ok(())
+ }
+
+ fn update(&mut self, _values: &[ScalarValue]) -> Result<()> {
+ unimplemented!("update_batch is implemented instead");
+ }
+
+ fn merge(&mut self, _states: &[ScalarValue]) -> Result<()> {
+ unimplemented!("merge_batch is implemented instead");
+ }
+
+ fn evaluate(&self) -> Result<ScalarValue> {
+ let covar = self.covar.evaluate()?;
+ let stddev1 = self.stddev1.evaluate()?;
+ let stddev2 = self.stddev2.evaluate()?;
+
+ if let ScalarValue::Float64(Some(c)) = covar {
+ if let ScalarValue::Float64(Some(s1)) = stddev1 {
+ if let ScalarValue::Float64(Some(s2)) = stddev2 {
+ return Ok(ScalarValue::Float64(Some(c / s1 / s2)));
Review comment:
They may be 0, pushed a fix. Thanks for finding this.
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[GitHub] [arrow-datafusion] realno commented on pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
realno commented on pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#issuecomment-1012836732
> why not support `covar_pop` and `covar_samp` together? reference https://www.postgresql.org/docs/14/functions-aggregate.html @realno
`covar_pop` and `covar_samp` were merged here https://github.com/apache/arrow-datafusion/pull/1551
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[GitHub] [arrow-datafusion] alamb commented on pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
alamb commented on pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#issuecomment-1013864306
Thanks @realno !
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[GitHub] [arrow-datafusion] Jimexist commented on a change in pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
Jimexist commented on a change in pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#discussion_r785383000
##########
File path: datafusion/src/physical_plan/expressions/correlation.rs
##########
@@ -0,0 +1,546 @@
+// 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::sync::Arc;
+
+use crate::error::{DataFusionError, Result};
+use crate::physical_plan::{
+ expressions::{covariance::CovarianceAccumulator, stddev::StddevAccumulator},
+ Accumulator, AggregateExpr, PhysicalExpr,
+};
+use crate::scalar::ScalarValue;
+use arrow::{array::ArrayRef, datatypes::DataType, datatypes::Field};
+
+use super::{format_state_name, StatsType};
+
+/// CORR aggregate expression
+#[derive(Debug)]
+pub struct Correlation {
+ name: String,
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+}
+
+/// function return type of correlation
+pub(crate) fn correlation_return_type(arg_type: &DataType) -> Result<DataType> {
+ match arg_type {
+ DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Float32
+ | DataType::Float64 => Ok(DataType::Float64),
+ other => Err(DataFusionError::Plan(format!(
+ "CORR does not support {:?}",
+ other
+ ))),
+ }
+}
+
+pub(crate) fn is_correlation_support_arg_type(arg_type: &DataType) -> bool {
+ matches!(
+ arg_type,
+ DataType::UInt8
+ | DataType::UInt16
+ | DataType::UInt32
+ | DataType::UInt64
+ | DataType::Int8
+ | DataType::Int16
+ | DataType::Int32
+ | DataType::Int64
+ | DataType::Float32
+ | DataType::Float64
+ )
+}
+
+impl Correlation {
+ /// Create a new COVAR_POP aggregate function
+ pub fn new(
+ expr1: Arc<dyn PhysicalExpr>,
+ expr2: Arc<dyn PhysicalExpr>,
+ name: impl Into<String>,
+ data_type: DataType,
+ ) -> Self {
+ // the result of correlation just support FLOAT64 data type.
+ assert!(matches!(data_type, DataType::Float64));
+ Self {
+ name: name.into(),
+ expr1,
+ expr2,
+ }
+ }
+}
+
+impl AggregateExpr for Correlation {
+ /// Return a reference to Any that can be used for downcasting
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn field(&self) -> Result<Field> {
+ Ok(Field::new(&self.name, DataType::Float64, true))
+ }
+
+ fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
+ Ok(Box::new(CorrelationAccumulator::try_new()?))
+ }
+
+ fn state_fields(&self) -> Result<Vec<Field>> {
+ Ok(vec![
+ Field::new(
+ &format_state_name(&self.name, "count"),
+ DataType::UInt64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_1"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "mean2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "m2_2"),
+ DataType::Float64,
+ true,
+ ),
+ Field::new(
+ &format_state_name(&self.name, "algo_const"),
+ DataType::Float64,
+ true,
+ ),
+ ])
+ }
+
+ fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
+ vec![self.expr1.clone(), self.expr2.clone()]
+ }
+
+ fn name(&self) -> &str {
+ &self.name
+ }
+}
+
+/// An accumulator to compute correlation
+#[derive(Debug)]
+pub struct CorrelationAccumulator {
+ covar: CovarianceAccumulator,
+ stddev1: StddevAccumulator,
+ stddev2: StddevAccumulator,
+}
+
+impl CorrelationAccumulator {
+ /// Creates a new `CorrelationAccumulator`
+ pub fn try_new() -> Result<Self> {
+ Ok(Self {
+ covar: CovarianceAccumulator::try_new(StatsType::Population)?,
+ stddev1: StddevAccumulator::try_new(StatsType::Population)?,
+ stddev2: StddevAccumulator::try_new(StatsType::Population)?,
+ })
+ }
+}
+
+impl Accumulator for CorrelationAccumulator {
+ fn state(&self) -> Result<Vec<ScalarValue>> {
+ Ok(vec![
+ ScalarValue::from(self.covar.get_count()),
+ ScalarValue::from(self.covar.get_mean1()),
+ ScalarValue::from(self.stddev1.get_m2()),
+ ScalarValue::from(self.covar.get_mean2()),
+ ScalarValue::from(self.stddev2.get_m2()),
+ ScalarValue::from(self.covar.get_algo_const()),
+ ])
+ }
+
+ fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+ self.covar.update_batch(values)?;
+ self.stddev1.update_batch(&[values[0].clone()])?;
+ self.stddev2.update_batch(&[values[1].clone()])?;
+ Ok(())
+ }
+
+ fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+ let states_c = [
+ states[0].clone(),
+ states[1].clone(),
+ states[3].clone(),
+ states[5].clone(),
+ ];
+ let states_s1 = [states[0].clone(), states[1].clone(), states[2].clone()];
+ let states_s2 = [states[0].clone(), states[3].clone(), states[4].clone()];
+
+ self.covar.merge_batch(&states_c)?;
+ self.stddev1.merge_batch(&states_s1)?;
+ self.stddev2.merge_batch(&states_s2)?;
+ Ok(())
+ }
+
+ fn update(&mut self, _values: &[ScalarValue]) -> Result<()> {
+ unimplemented!("update_batch is implemented instead");
+ }
+
+ fn merge(&mut self, _states: &[ScalarValue]) -> Result<()> {
+ unimplemented!("merge_batch is implemented instead");
+ }
+
+ fn evaluate(&self) -> Result<ScalarValue> {
+ let covar = self.covar.evaluate()?;
+ let stddev1 = self.stddev1.evaluate()?;
+ let stddev2 = self.stddev2.evaluate()?;
+
+ if let ScalarValue::Float64(Some(c)) = covar {
+ if let ScalarValue::Float64(Some(s1)) = stddev1 {
+ if let ScalarValue::Float64(Some(s2)) = stddev2 {
+ return Ok(ScalarValue::Float64(Some(c / s1 / s2)));
Review comment:
can s1 or s2 be 0?
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[GitHub] [arrow-datafusion] alamb merged pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
alamb merged pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561
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[GitHub] [arrow-datafusion] liukun4515 commented on pull request #1561: add correlation function
Posted by GitBox <gi...@apache.org>.
liukun4515 commented on pull request #1561:
URL: https://github.com/apache/arrow-datafusion/pull/1561#issuecomment-1012834188
why not support `covar_pop` and `covar_samp` togethe?
reference https://www.postgresql.org/docs/14/functions-aggregate.html
@realno
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