jackwener commented on code in PR #7544:
URL: https://github.com/apache/arrow-datafusion/pull/7544#discussion_r1324866471
##########
datafusion/common/src/stats.rs:
##########
@@ -70,3 +72,29 @@ pub struct ColumnStatistics {
/// Number of distinct values
pub distinct_count: Option<usize>,
}
+
+impl ColumnStatistics {
+ /// Returns the [`Vec<ColumnStatistics>`] corresponding to the given
schema by assigning
+ /// infinite bounds to each column in the schema. This is useful when even
the input statistics
+ /// are not known, as the current executor can shrink the bounds of some
columns.
+ pub fn new_with_unbounded_columns(schema: SchemaRef) ->
Vec<ColumnStatistics> {
+ let data_types = schema
+ .fields()
+ .iter()
+ .map(|field| field.data_type())
+ .collect::<Vec<_>>();
+
+ data_types
+ .into_iter()
+ .map(|data_type| {
+ let dt = ScalarValue::try_from(data_type.clone()).ok();
+ ColumnStatistics {
+ null_count: None,
+ max_value: dt.clone(),
+ min_value: dt,
Review Comment:
🤔In my opinion, `min_value`/`max_value` is set as
`ScalarValue<XXType<None>>` is used to get datatype of this column. Is right?
##########
datafusion/common/src/stats.rs:
##########
@@ -70,3 +72,29 @@ pub struct ColumnStatistics {
/// Number of distinct values
pub distinct_count: Option<usize>,
}
+
+impl ColumnStatistics {
+ /// Returns the [`Vec<ColumnStatistics>`] corresponding to the given
schema by assigning
+ /// infinite bounds to each column in the schema. This is useful when even
the input statistics
+ /// are not known, as the current executor can shrink the bounds of some
columns.
+ pub fn new_with_unbounded_columns(schema: SchemaRef) ->
Vec<ColumnStatistics> {
+ let data_types = schema
+ .fields()
+ .iter()
+ .map(|field| field.data_type())
+ .collect::<Vec<_>>();
+
+ data_types
+ .into_iter()
+ .map(|data_type| {
+ let dt = ScalarValue::try_from(data_type.clone()).ok();
+ ColumnStatistics {
+ null_count: None,
+ max_value: dt.clone(),
+ min_value: dt,
Review Comment:
🤔In my opinion, `min_value`/`max_value` is set as
`ScalarValue<XXType<None>>` is used to get datatype of this column. Is right?
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