Revert "chore: remove panics in datafusion-common::scalar (apache#7901)"

This reverts commit e642cc2.
alamb · Nov 12, 2023 · f3fca2b · f3fca2b
1 parent 6fe00ce
commit f3fca2b
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Showing 54 changed files with 427 additions and 723 deletions.
diff --git a/datafusion/common/src/pyarrow.rs b/datafusion/common/src/pyarrow.rs
@@ -54,7 +54,7 @@ impl FromPyArrow for ScalarValue {
 
 impl ToPyArrow for ScalarValue {
     fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
-        let array = self.to_array()?;
+        let array = self.to_array();
         // convert to pyarrow array using C data interface
         let pyarray = array.to_data().to_pyarrow(py)?;
         let pyscalar = pyarray.call_method1(py, "__getitem__", (0,))?;

diff --git a/datafusion/common/src/scalar.rs b/datafusion/common/src/scalar.rs
diff --git a/datafusion/core/benches/scalar.rs b/datafusion/core/benches/scalar.rs
@@ -22,15 +22,7 @@ fn criterion_benchmark(c: &mut Criterion) {
     c.bench_function("to_array_of_size 100000", |b| {
         let scalar = ScalarValue::Int32(Some(100));
 
-        b.iter(|| {
-            assert_eq!(
-                scalar
-                    .to_array_of_size(100000)
-                    .expect("Failed to convert to array of size")
-                    .null_count(),
-                0
-            )
-        })
+        b.iter(|| assert_eq!(scalar.to_array_of_size(100000).null_count(), 0))
     });
 }
 

diff --git a/datafusion/core/src/datasource/listing/helpers.rs b/datafusion/core/src/datasource/listing/helpers.rs
@@ -276,10 +276,7 @@ async fn prune_partitions(
     // Applies `filter` to `batch` returning `None` on error
     let do_filter = |filter| -> Option<ArrayRef> {
         let expr = create_physical_expr(filter, &df_schema, &schema, &props).ok()?;
-        expr.evaluate(&batch)
-            .ok()?
-            .into_array(partitions.len())
-            .ok()
+        Some(expr.evaluate(&batch).ok()?.into_array(partitions.len()))
     };
 
     //.Compute the conjunction of the filters, ignoring errors

diff --git a/datafusion/core/src/datasource/physical_plan/file_scan_config.rs b/datafusion/core/src/datasource/physical_plan/file_scan_config.rs
@@ -336,7 +336,7 @@ impl PartitionColumnProjector {
                     &mut self.key_buffer_cache,
                     partition_value.as_ref(),
                     file_batch.num_rows(),
-                )?,
+                ),
             )
         }
 
@@ -396,11 +396,11 @@ fn create_dict_array<T>(
     dict_val: &ScalarValue,
     len: usize,
     data_type: DataType,
-) -> Result<ArrayRef>
+) -> ArrayRef
 where
     T: ArrowNativeType,
 {
-    let dict_vals = dict_val.to_array()?;
+    let dict_vals = dict_val.to_array();
 
     let sliced_key_buffer = buffer_gen.get_buffer(len);
 
@@ -409,16 +409,16 @@ where
         .len(len)
         .add_buffer(sliced_key_buffer);
     builder = builder.add_child_data(dict_vals.to_data());
-    Ok(Arc::new(DictionaryArray::<UInt16Type>::from(
+    Arc::new(DictionaryArray::<UInt16Type>::from(
         builder.build().unwrap(),
-    )))
+    ))
 }
 
 fn create_output_array(
     key_buffer_cache: &mut ZeroBufferGenerators,
     val: &ScalarValue,
     len: usize,
-) -> Result<ArrayRef> {
+) -> ArrayRef {
     if let ScalarValue::Dictionary(key_type, dict_val) = &val {
         match key_type.as_ref() {
             DataType::Int8 => {

diff --git a/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs b/datafusion/core/src/datasource/physical_plan/parquet/row_filter.rs
@@ -126,7 +126,7 @@ impl ArrowPredicate for DatafusionArrowPredicate {
         match self
             .physical_expr
             .evaluate(&batch)
-            .and_then(|v| v.into_array(batch.num_rows()))
+            .map(|v| v.into_array(batch.num_rows()))
         {
             Ok(array) => {
                 let bool_arr = as_boolean_array(&array)?.clone();

diff --git a/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs b/datafusion/core/src/datasource/physical_plan/parquet/row_groups.rs
@@ -405,7 +405,7 @@ macro_rules! get_min_max_values {
             .flatten()
             // column either didn't have statistics at all or didn't have min/max values
             .or_else(|| Some(null_scalar.clone()))
-            .and_then(|s| s.to_array().ok())
+            .map(|s| s.to_array())
     }}
 }
 
@@ -425,7 +425,7 @@ macro_rules! get_null_count_values {
             },
         );
 
-        value.to_array().ok()
+        Some(value.to_array())
     }};
 }
 

diff --git a/datafusion/expr/src/columnar_value.rs b/datafusion/expr/src/columnar_value.rs
@@ -20,7 +20,7 @@
 use arrow::array::ArrayRef;
 use arrow::array::NullArray;
 use arrow::datatypes::DataType;
-use datafusion_common::{Result, ScalarValue};
+use datafusion_common::ScalarValue;
 use std::sync::Arc;
 
 /// Represents the result of evaluating an expression: either a single
@@ -47,15 +47,11 @@ impl ColumnarValue {
 
     /// Convert a columnar value into an ArrayRef. [`Self::Scalar`] is
     /// converted by repeating the same scalar multiple times.
-    ///
-    /// # Errors
-    ///
-    /// Errors if `self` is a Scalar that fails to be converted into an array of size
-    pub fn into_array(self, num_rows: usize) -> Result<ArrayRef> {
-        Ok(match self {
+    pub fn into_array(self, num_rows: usize) -> ArrayRef {
+        match self {
             ColumnarValue::Array(array) => array,
-            ColumnarValue::Scalar(scalar) => scalar.to_array_of_size(num_rows)?,
-        })
+            ColumnarValue::Scalar(scalar) => scalar.to_array_of_size(num_rows),
+        }
     }
 
     /// null columnar values are implemented as a null array in order to pass batch

diff --git a/datafusion/expr/src/window_state.rs b/datafusion/expr/src/window_state.rs
@@ -98,7 +98,7 @@ impl WindowAggState {
     }
 
     pub fn new(out_type: &DataType) -> Result<Self> {
-        let empty_out_col = ScalarValue::try_from(out_type)?.to_array_of_size(0)?;
+        let empty_out_col = ScalarValue::try_from(out_type)?.to_array_of_size(0);
         Ok(Self {
             window_frame_range: Range { start: 0, end: 0 },
             window_frame_ctx: None,

diff --git a/datafusion/optimizer/src/unwrap_cast_in_comparison.rs b/datafusion/optimizer/src/unwrap_cast_in_comparison.rs
@@ -1089,12 +1089,8 @@ mod tests {
                 // Verify that calling the arrow
                 // cast kernel yields the same results
                 // input array
-                let literal_array = literal
-                    .to_array_of_size(1)
-                    .expect("Failed to convert to array of size");
-                let expected_array = expected_value
-                    .to_array_of_size(1)
-                    .expect("Failed to convert to array of size");
+                let literal_array = literal.to_array_of_size(1);
+                let expected_array = expected_value.to_array_of_size(1);
                 let cast_array = cast_with_options(
                     &literal_array,
                     &target_type,

diff --git a/datafusion/physical-expr/src/aggregate/correlation.rs b/datafusion/physical-expr/src/aggregate/correlation.rs
@@ -505,17 +505,13 @@ mod tests {
 
         let values1 = expr1
             .iter()
-            .map(|e| {
-                e.evaluate(batch1)
-                    .and_then(|v| v.into_array(batch1.num_rows()))
-            })
+            .map(|e| e.evaluate(batch1))
+            .map(|r| r.map(|v| v.into_array(batch1.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         let values2 = expr2
             .iter()
-            .map(|e| {
-                e.evaluate(batch2)
-                    .and_then(|v| v.into_array(batch2.num_rows()))
-            })
+            .map(|e| e.evaluate(batch2))
+            .map(|r| r.map(|v| v.into_array(batch2.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         accum1.update_batch(&values1)?;
         accum2.update_batch(&values2)?;

diff --git a/datafusion/physical-expr/src/aggregate/covariance.rs b/datafusion/physical-expr/src/aggregate/covariance.rs
@@ -754,17 +754,13 @@ mod tests {
 
         let values1 = expr1
             .iter()
-            .map(|e| {
-                e.evaluate(batch1)
-                    .and_then(|v| v.into_array(batch1.num_rows()))
-            })
+            .map(|e| e.evaluate(batch1))
+            .map(|r| r.map(|v| v.into_array(batch1.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         let values2 = expr2
             .iter()
-            .map(|e| {
-                e.evaluate(batch2)
-                    .and_then(|v| v.into_array(batch2.num_rows()))
-            })
+            .map(|e| e.evaluate(batch2))
+            .map(|r| r.map(|v| v.into_array(batch2.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         accum1.update_batch(&values1)?;
         accum2.update_batch(&values2)?;

diff --git a/datafusion/physical-expr/src/aggregate/first_last.rs b/datafusion/physical-expr/src/aggregate/first_last.rs
@@ -587,10 +587,7 @@ mod tests {
         let mut states = vec![];
 
         for idx in 0..state1.len() {
-            states.push(concat(&[
-                &state1[idx].to_array()?,
-                &state2[idx].to_array()?,
-            ])?);
+            states.push(concat(&[&state1[idx].to_array(), &state2[idx].to_array()])?);
         }
 
         let mut first_accumulator =
@@ -617,10 +614,7 @@ mod tests {
         let mut states = vec![];
 
         for idx in 0..state1.len() {
-            states.push(concat(&[
-                &state1[idx].to_array()?,
-                &state2[idx].to_array()?,
-            ])?);
+            states.push(concat(&[&state1[idx].to_array(), &state2[idx].to_array()])?);
         }
 
         let mut last_accumulator =

diff --git a/datafusion/physical-expr/src/aggregate/stddev.rs b/datafusion/physical-expr/src/aggregate/stddev.rs
@@ -445,17 +445,13 @@ mod tests {
 
         let values1 = expr1
             .iter()
-            .map(|e| {
-                e.evaluate(batch1)
-                    .and_then(|v| v.into_array(batch1.num_rows()))
-            })
+            .map(|e| e.evaluate(batch1))
+            .map(|r| r.map(|v| v.into_array(batch1.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         let values2 = expr2
             .iter()
-            .map(|e| {
-                e.evaluate(batch2)
-                    .and_then(|v| v.into_array(batch2.num_rows()))
-            })
+            .map(|e| e.evaluate(batch2))
+            .map(|r| r.map(|v| v.into_array(batch2.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         accum1.update_batch(&values1)?;
         accum2.update_batch(&values2)?;

diff --git a/datafusion/physical-expr/src/aggregate/utils.rs b/datafusion/physical-expr/src/aggregate/utils.rs
@@ -36,11 +36,11 @@ use std::sync::Arc;
 pub fn get_accum_scalar_values_as_arrays(
     accum: &dyn Accumulator,
 ) -> Result<Vec<ArrayRef>> {
-    accum
+    Ok(accum
         .state()?
         .iter()
         .map(|s| s.to_array_of_size(1))
-        .collect::<Result<Vec<_>>>()
+        .collect::<Vec<_>>())
 }
 
 /// Computes averages for `Decimal128`/`Decimal256` values, checking for overflow

diff --git a/datafusion/physical-expr/src/aggregate/variance.rs b/datafusion/physical-expr/src/aggregate/variance.rs
@@ -519,17 +519,13 @@ mod tests {
 
         let values1 = expr1
             .iter()
-            .map(|e| {
-                e.evaluate(batch1)
-                    .and_then(|v| v.into_array(batch1.num_rows()))
-            })
+            .map(|e| e.evaluate(batch1))
+            .map(|r| r.map(|v| v.into_array(batch1.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         let values2 = expr2
             .iter()
-            .map(|e| {
-                e.evaluate(batch2)
-                    .and_then(|v| v.into_array(batch2.num_rows()))
-            })
+            .map(|e| e.evaluate(batch2))
+            .map(|r| r.map(|v| v.into_array(batch2.num_rows())))
             .collect::<Result<Vec<_>>>()?;
         accum1.update_batch(&values1)?;
         accum2.update_batch(&values2)?;

diff --git a/datafusion/physical-expr/src/conditional_expressions.rs b/datafusion/physical-expr/src/conditional_expressions.rs
@@ -54,7 +54,7 @@ pub fn coalesce(args: &[ColumnarValue]) -> Result<ColumnarValue> {
                     if value.is_null() {
                         continue;
                     } else {
-                        let last_value = value.to_array_of_size(size)?;
+                        let last_value = value.to_array_of_size(size);
                         current_value =
                             zip(&remainder, &last_value, current_value.as_ref())?;
                         break;

diff --git a/datafusion/physical-expr/src/datetime_expressions.rs b/datafusion/physical-expr/src/datetime_expressions.rs
@@ -852,7 +852,7 @@ pub fn date_part(args: &[ColumnarValue]) -> Result<ColumnarValue> {
 
     let array = match array {
         ColumnarValue::Array(array) => array.clone(),
-        ColumnarValue::Scalar(scalar) => scalar.to_array()?,
+        ColumnarValue::Scalar(scalar) => scalar.to_array(),
     };
 
     let arr = match date_part.to_lowercase().as_str() {