alamb commented on code in PR #2587:
URL: https://github.com/apache/arrow-datafusion/pull/2587#discussion_r879772780
##########
datafusion/jit/src/api.rs:
##########
@@ -604,6 +606,15 @@ impl<'a> CodeBlock<'a> {
internal_err!("No func with the name {} exist", fn_name)
}
}
+
+ pub fn deref(&self, ptr: Expr, ty: JITType) -> Result<Expr> {
+ Ok(Expr::Deref(Box::new(ptr), ty))
+ }
+
+ pub fn store(&mut self, value: Expr, ptr: Expr) -> Result<()> {
Review Comment:
```suggestion
/// Store the value in `value` to the address in `ptr`
pub fn store(&mut self, value: Expr, ptr: Expr) -> Result<()> {
```
##########
datafusion/jit/src/compile.rs:
##########
@@ -0,0 +1,184 @@
+// 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.
+
+//! Compile DataFusion Expr to JIT'd function.
+
+use datafusion_common::Result;
+
+use crate::api::Assembler;
+use crate::{
+ api::GeneratedFunction,
+ ast::{Expr as JITExpr, I64, PTR_SIZE},
+};
+
+/// Wrap JIT Expr to array compute function.
+pub fn build_calc_fn(
+ assembler: &Assembler,
+ jit_expr: JITExpr,
+ input_names: Vec<String>,
+) -> Result<GeneratedFunction> {
+ let mut builder = assembler.new_func_builder("calc_fn");
+ for input in &input_names {
+ builder = builder.param(format!("{}_array", input), I64);
+ }
+ let mut builder = builder.param("result", I64).param("len", I64);
+
+ let mut fn_body = builder.enter_block();
+ fn_body.declare_as("index", fn_body.lit_i(0))?;
+ fn_body.while_block(
+ |cond| cond.lt(cond.id("index")?, cond.id("len")?),
+ |w| {
+ w.declare_as("offset", w.mul(w.id("index")?, w.lit_i(PTR_SIZE as
i64))?)?;
+ for input in &input_names {
+ w.declare_as(
+ format!("{}_ptr", input),
+ w.add(w.id(format!("{}_array", input))?, w.id("offset")?)?,
+ )?;
+ w.declare_as(input, w.deref(w.id(format!("{}_ptr", input))?,
I64)?)?;
+ }
+ w.declare_as("res_ptr", w.add(w.id("result")?, w.id("offset")?)?)?;
+ w.declare_as("res", jit_expr.clone())?;
+ w.store(w.id("res")?, w.id("res_ptr")?)?;
+
+ w.assign("index", w.add(w.id("index")?, w.lit_i(1))?)?;
+ Ok(())
+ },
+ )?;
+
+ let gen_func = fn_body.build();
+ Ok(gen_func)
+}
+
+#[cfg(test)]
+mod test {
+ use std::{collections::HashMap, sync::Arc};
+
+ use arrow::{
+ array::{Array, PrimitiveArray},
+ datatypes::{DataType, Int64Type},
+ };
+ use datafusion_common::{DFField, DFSchema, DataFusionError};
+ use datafusion_expr::Expr as DFExpr;
+
+ use crate::ast::BinaryExpr;
+
+ use super::*;
+
+ fn run_df_expr(
Review Comment:
In the longer term I would like to see this type of logic encapsulated
somehow
So we would have a function or struct that took an `Expr` and several
`ArrayRefs` and then called a JIT or non-JIT version of evaluation depending on
flags or options.
##########
datafusion/jit/src/compile.rs:
##########
@@ -0,0 +1,184 @@
+// 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.
+
+//! Compile DataFusion Expr to JIT'd function.
+
+use datafusion_common::Result;
+
+use crate::api::Assembler;
+use crate::{
+ api::GeneratedFunction,
+ ast::{Expr as JITExpr, I64, PTR_SIZE},
+};
+
+/// Wrap JIT Expr to array compute function.
+pub fn build_calc_fn(
+ assembler: &Assembler,
+ jit_expr: JITExpr,
+ input_names: Vec<String>,
+) -> Result<GeneratedFunction> {
+ let mut builder = assembler.new_func_builder("calc_fn");
+ for input in &input_names {
+ builder = builder.param(format!("{}_array", input), I64);
+ }
+ let mut builder = builder.param("result", I64).param("len", I64);
+
+ let mut fn_body = builder.enter_block();
+ fn_body.declare_as("index", fn_body.lit_i(0))?;
+ fn_body.while_block(
+ |cond| cond.lt(cond.id("index")?, cond.id("len")?),
+ |w| {
+ w.declare_as("offset", w.mul(w.id("index")?, w.lit_i(PTR_SIZE as
i64))?)?;
+ for input in &input_names {
+ w.declare_as(
+ format!("{}_ptr", input),
+ w.add(w.id(format!("{}_array", input))?, w.id("offset")?)?,
+ )?;
+ w.declare_as(input, w.deref(w.id(format!("{}_ptr", input))?,
I64)?)?;
+ }
+ w.declare_as("res_ptr", w.add(w.id("result")?, w.id("offset")?)?)?;
+ w.declare_as("res", jit_expr.clone())?;
+ w.store(w.id("res")?, w.id("res_ptr")?)?;
+
+ w.assign("index", w.add(w.id("index")?, w.lit_i(1))?)?;
+ Ok(())
+ },
+ )?;
+
+ let gen_func = fn_body.build();
+ Ok(gen_func)
+}
+
+#[cfg(test)]
+mod test {
+ use std::{collections::HashMap, sync::Arc};
+
+ use arrow::{
+ array::{Array, PrimitiveArray},
+ datatypes::{DataType, Int64Type},
+ };
+ use datafusion_common::{DFField, DFSchema, DataFusionError};
+ use datafusion_expr::Expr as DFExpr;
+
+ use crate::ast::BinaryExpr;
+
+ use super::*;
+
+ fn run_df_expr(
+ df_expr: DFExpr,
+ schema: Arc<DFSchema>,
+ lhs: PrimitiveArray<Int64Type>,
+ rhs: PrimitiveArray<Int64Type>,
+ ) -> Result<PrimitiveArray<Int64Type>> {
+ if lhs.null_count() != 0 || rhs.null_count() != 0 {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on nullable array not yet supported".to_string(),
+ ));
+ }
+ if lhs.len() != rhs.len() {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on different length arrays not yet
supported".to_string(),
+ ));
+ }
+
+ // translate DF Expr to JIT Expr
+ let input_fields = schema.field_names();
+ let jit_expr: JITExpr = (df_expr, schema).try_into()?;
+
+ // allocate memory for calc result
+ let len = lhs.len();
+ let result = vec![0i64; len];
+
+ // compile and run JIT code
+ let assembler = Assembler::default();
+ let gen_func = build_calc_fn(&assembler, jit_expr, input_fields)?;
+ let mut jit = assembler.create_jit();
+ let code_ptr = jit.compile(gen_func)?;
+ let code_fn =
+ unsafe { core::mem::transmute::<_, fn(i64, i64, i64, i64) ->
()>(code_ptr) };
Review Comment:
I wonder why not cast to the types you really want, like `fn(*i64, *i64,
*i64, i64)` and then you can avoid the `as i64` stuff below
##########
datafusion/jit/src/compile.rs:
##########
@@ -0,0 +1,184 @@
+// 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.
+
+//! Compile DataFusion Expr to JIT'd function.
+
+use datafusion_common::Result;
+
+use crate::api::Assembler;
+use crate::{
+ api::GeneratedFunction,
+ ast::{Expr as JITExpr, I64, PTR_SIZE},
+};
+
+/// Wrap JIT Expr to array compute function.
+pub fn build_calc_fn(
+ assembler: &Assembler,
+ jit_expr: JITExpr,
+ input_names: Vec<String>,
+) -> Result<GeneratedFunction> {
+ let mut builder = assembler.new_func_builder("calc_fn");
+ for input in &input_names {
+ builder = builder.param(format!("{}_array", input), I64);
+ }
+ let mut builder = builder.param("result", I64).param("len", I64);
+
+ let mut fn_body = builder.enter_block();
+ fn_body.declare_as("index", fn_body.lit_i(0))?;
+ fn_body.while_block(
+ |cond| cond.lt(cond.id("index")?, cond.id("len")?),
+ |w| {
+ w.declare_as("offset", w.mul(w.id("index")?, w.lit_i(PTR_SIZE as
i64))?)?;
+ for input in &input_names {
+ w.declare_as(
+ format!("{}_ptr", input),
+ w.add(w.id(format!("{}_array", input))?, w.id("offset")?)?,
+ )?;
+ w.declare_as(input, w.deref(w.id(format!("{}_ptr", input))?,
I64)?)?;
+ }
+ w.declare_as("res_ptr", w.add(w.id("result")?, w.id("offset")?)?)?;
+ w.declare_as("res", jit_expr.clone())?;
+ w.store(w.id("res")?, w.id("res_ptr")?)?;
+
+ w.assign("index", w.add(w.id("index")?, w.lit_i(1))?)?;
+ Ok(())
+ },
+ )?;
+
+ let gen_func = fn_body.build();
+ Ok(gen_func)
+}
+
+#[cfg(test)]
+mod test {
+ use std::{collections::HashMap, sync::Arc};
+
+ use arrow::{
+ array::{Array, PrimitiveArray},
+ datatypes::{DataType, Int64Type},
+ };
+ use datafusion_common::{DFField, DFSchema, DataFusionError};
+ use datafusion_expr::Expr as DFExpr;
+
+ use crate::ast::BinaryExpr;
+
+ use super::*;
+
+ fn run_df_expr(
+ df_expr: DFExpr,
+ schema: Arc<DFSchema>,
+ lhs: PrimitiveArray<Int64Type>,
+ rhs: PrimitiveArray<Int64Type>,
+ ) -> Result<PrimitiveArray<Int64Type>> {
+ if lhs.null_count() != 0 || rhs.null_count() != 0 {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on nullable array not yet supported".to_string(),
+ ));
+ }
+ if lhs.len() != rhs.len() {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on different length arrays not yet
supported".to_string(),
+ ));
+ }
+
+ // translate DF Expr to JIT Expr
+ let input_fields = schema.field_names();
+ let jit_expr: JITExpr = (df_expr, schema).try_into()?;
+
+ // allocate memory for calc result
+ let len = lhs.len();
+ let result = vec![0i64; len];
+
+ // compile and run JIT code
+ let assembler = Assembler::default();
+ let gen_func = build_calc_fn(&assembler, jit_expr, input_fields)?;
+ let mut jit = assembler.create_jit();
+ let code_ptr = jit.compile(gen_func)?;
+ let code_fn =
+ unsafe { core::mem::transmute::<_, fn(i64, i64, i64, i64) ->
()>(code_ptr) };
+ code_fn(
+ lhs.values().as_ptr() as i64,
+ rhs.values().as_ptr() as i64,
+ result.as_ptr() as i64,
+ len as i64,
+ );
+
+ let result_array = PrimitiveArray::<Int64Type>::from_iter(result);
+ Ok(result_array)
+ }
+
+ #[test]
+ fn array_add() {
+ let array_a: PrimitiveArray<Int64Type> =
Review Comment:
I recommend using different values for `array_a` and `array_b` so issues in
argument handling would be evident
Like maybe
```rust
let array_b: PrimitiveArray<Int64Type> =
PrimitiveArray::from_iter_values((10..20).map(|x| x + 1));
```
##########
datafusion/jit/src/api.rs:
##########
@@ -604,6 +606,15 @@ impl<'a> CodeBlock<'a> {
internal_err!("No func with the name {} exist", fn_name)
}
}
+
+ pub fn deref(&self, ptr: Expr, ty: JITType) -> Result<Expr> {
Review Comment:
What do you think about adding docstrings?
```suggestion
/// Return the value pointed to by the ptr stored in `ptr`
pub fn deref(&self, ptr: Expr, ty: JITType) -> Result<Expr> {
```
##########
datafusion/jit/src/compile.rs:
##########
@@ -0,0 +1,184 @@
+// 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.
+
+//! Compile DataFusion Expr to JIT'd function.
+
+use datafusion_common::Result;
+
+use crate::api::Assembler;
+use crate::{
+ api::GeneratedFunction,
+ ast::{Expr as JITExpr, I64, PTR_SIZE},
+};
+
+/// Wrap JIT Expr to array compute function.
+pub fn build_calc_fn(
+ assembler: &Assembler,
+ jit_expr: JITExpr,
+ input_names: Vec<String>,
+) -> Result<GeneratedFunction> {
+ let mut builder = assembler.new_func_builder("calc_fn");
+ for input in &input_names {
+ builder = builder.param(format!("{}_array", input), I64);
+ }
+ let mut builder = builder.param("result", I64).param("len", I64);
+
+ let mut fn_body = builder.enter_block();
+ fn_body.declare_as("index", fn_body.lit_i(0))?;
+ fn_body.while_block(
+ |cond| cond.lt(cond.id("index")?, cond.id("len")?),
+ |w| {
+ w.declare_as("offset", w.mul(w.id("index")?, w.lit_i(PTR_SIZE as
i64))?)?;
+ for input in &input_names {
+ w.declare_as(
+ format!("{}_ptr", input),
+ w.add(w.id(format!("{}_array", input))?, w.id("offset")?)?,
+ )?;
+ w.declare_as(input, w.deref(w.id(format!("{}_ptr", input))?,
I64)?)?;
+ }
+ w.declare_as("res_ptr", w.add(w.id("result")?, w.id("offset")?)?)?;
+ w.declare_as("res", jit_expr.clone())?;
+ w.store(w.id("res")?, w.id("res_ptr")?)?;
+
+ w.assign("index", w.add(w.id("index")?, w.lit_i(1))?)?;
+ Ok(())
+ },
+ )?;
+
+ let gen_func = fn_body.build();
+ Ok(gen_func)
+}
+
+#[cfg(test)]
+mod test {
+ use std::{collections::HashMap, sync::Arc};
+
+ use arrow::{
+ array::{Array, PrimitiveArray},
+ datatypes::{DataType, Int64Type},
+ };
+ use datafusion_common::{DFField, DFSchema, DataFusionError};
+ use datafusion_expr::Expr as DFExpr;
+
+ use crate::ast::BinaryExpr;
+
+ use super::*;
+
+ fn run_df_expr(
+ df_expr: DFExpr,
+ schema: Arc<DFSchema>,
+ lhs: PrimitiveArray<Int64Type>,
+ rhs: PrimitiveArray<Int64Type>,
+ ) -> Result<PrimitiveArray<Int64Type>> {
+ if lhs.null_count() != 0 || rhs.null_count() != 0 {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on nullable array not yet supported".to_string(),
+ ));
+ }
+ if lhs.len() != rhs.len() {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on different length arrays not yet
supported".to_string(),
+ ));
+ }
+
+ // translate DF Expr to JIT Expr
+ let input_fields = schema.field_names();
+ let jit_expr: JITExpr = (df_expr, schema).try_into()?;
+
+ // allocate memory for calc result
+ let len = lhs.len();
+ let result = vec![0i64; len];
+
+ // compile and run JIT code
+ let assembler = Assembler::default();
+ let gen_func = build_calc_fn(&assembler, jit_expr, input_fields)?;
+ let mut jit = assembler.create_jit();
+ let code_ptr = jit.compile(gen_func)?;
+ let code_fn =
+ unsafe { core::mem::transmute::<_, fn(i64, i64, i64, i64) ->
()>(code_ptr) };
+ code_fn(
+ lhs.values().as_ptr() as i64,
+ rhs.values().as_ptr() as i64,
+ result.as_ptr() as i64,
+ len as i64,
+ );
+
+ let result_array = PrimitiveArray::<Int64Type>::from_iter(result);
+ Ok(result_array)
+ }
+
+ #[test]
+ fn array_add() {
+ let array_a: PrimitiveArray<Int64Type> =
+ PrimitiveArray::from_iter_values((0..10).map(|x| x + 1));
+ let array_b: PrimitiveArray<Int64Type> =
+ PrimitiveArray::from_iter_values((0..10).map(|x| x + 1));
+ let expected =
+ arrow::compute::kernels::arithmetic::add(&array_a,
&array_b).unwrap();
+
+ let df_expr = datafusion_expr::col("a") + datafusion_expr::col("b");
+ let schema = Arc::new(
+ DFSchema::new_with_metadata(
+ vec![
+ DFField::new(Some("table1"), "a", DataType::Int64, false),
+ DFField::new(Some("table1"), "b", DataType::Int64, false),
+ ],
+ HashMap::new(),
+ )
+ .unwrap(),
+ );
+
+ let result = run_df_expr(df_expr, schema, array_a, array_b).unwrap();
+ assert_eq!(result, expected);
+ }
+
+ #[test]
+ fn calc_fn_builder() {
+ let expr = JITExpr::Binary(BinaryExpr::Add(
+ Box::new(JITExpr::Identifier("table1.a".to_string(), I64)),
+ Box::new(JITExpr::Identifier("table1.b".to_string(), I64)),
+ ));
+ let fields = vec!["table1.a".to_string(), "table1.b".to_string()];
+
+ let expected = r#"fn calc_fn_0(table1.a_array: i64, table1.b_array:
i64, result: i64, len: i64) -> () {
+ let index: i64;
+ index = 0;
+ while index < len {
Review Comment:
I looked at this code and it looks 👍 to me
##########
datafusion/jit/src/compile.rs:
##########
@@ -0,0 +1,184 @@
+// 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.
+
+//! Compile DataFusion Expr to JIT'd function.
+
+use datafusion_common::Result;
+
+use crate::api::Assembler;
+use crate::{
+ api::GeneratedFunction,
+ ast::{Expr as JITExpr, I64, PTR_SIZE},
+};
+
+/// Wrap JIT Expr to array compute function.
+pub fn build_calc_fn(
+ assembler: &Assembler,
+ jit_expr: JITExpr,
+ input_names: Vec<String>,
+) -> Result<GeneratedFunction> {
+ let mut builder = assembler.new_func_builder("calc_fn");
+ for input in &input_names {
+ builder = builder.param(format!("{}_array", input), I64);
+ }
+ let mut builder = builder.param("result", I64).param("len", I64);
+
+ let mut fn_body = builder.enter_block();
+ fn_body.declare_as("index", fn_body.lit_i(0))?;
+ fn_body.while_block(
+ |cond| cond.lt(cond.id("index")?, cond.id("len")?),
+ |w| {
+ w.declare_as("offset", w.mul(w.id("index")?, w.lit_i(PTR_SIZE as
i64))?)?;
+ for input in &input_names {
+ w.declare_as(
+ format!("{}_ptr", input),
+ w.add(w.id(format!("{}_array", input))?, w.id("offset")?)?,
+ )?;
+ w.declare_as(input, w.deref(w.id(format!("{}_ptr", input))?,
I64)?)?;
+ }
+ w.declare_as("res_ptr", w.add(w.id("result")?, w.id("offset")?)?)?;
+ w.declare_as("res", jit_expr.clone())?;
+ w.store(w.id("res")?, w.id("res_ptr")?)?;
+
+ w.assign("index", w.add(w.id("index")?, w.lit_i(1))?)?;
+ Ok(())
+ },
+ )?;
+
+ let gen_func = fn_body.build();
+ Ok(gen_func)
+}
+
+#[cfg(test)]
+mod test {
+ use std::{collections::HashMap, sync::Arc};
+
+ use arrow::{
+ array::{Array, PrimitiveArray},
+ datatypes::{DataType, Int64Type},
+ };
+ use datafusion_common::{DFField, DFSchema, DataFusionError};
+ use datafusion_expr::Expr as DFExpr;
+
+ use crate::ast::BinaryExpr;
+
+ use super::*;
+
+ fn run_df_expr(
+ df_expr: DFExpr,
+ schema: Arc<DFSchema>,
+ lhs: PrimitiveArray<Int64Type>,
+ rhs: PrimitiveArray<Int64Type>,
+ ) -> Result<PrimitiveArray<Int64Type>> {
+ if lhs.null_count() != 0 || rhs.null_count() != 0 {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on nullable array not yet supported".to_string(),
+ ));
+ }
+ if lhs.len() != rhs.len() {
+ return Err(DataFusionError::NotImplemented(
+ "Computing on different length arrays not yet
supported".to_string(),
+ ));
+ }
+
+ // translate DF Expr to JIT Expr
+ let input_fields = schema.field_names();
+ let jit_expr: JITExpr = (df_expr, schema).try_into()?;
+
+ // allocate memory for calc result
+ let len = lhs.len();
+ let result = vec![0i64; len];
+
+ // compile and run JIT code
+ let assembler = Assembler::default();
+ let gen_func = build_calc_fn(&assembler, jit_expr, input_fields)?;
+ let mut jit = assembler.create_jit();
+ let code_ptr = jit.compile(gen_func)?;
+ let code_fn =
+ unsafe { core::mem::transmute::<_, fn(i64, i64, i64, i64) ->
()>(code_ptr) };
Review Comment:
code like this is some of my favorite ❤️ -- cast some memory to a function
pointer and call it ;)
Extremely unsafe but feels very powerful
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