Jefffrey commented on code in PR #19829:
URL: https://github.com/apache/datafusion/pull/19829#discussion_r2698572815
##########
datafusion/functions/src/datetime/date_trunc.rs:
##########
@@ -221,6 +223,7 @@ impl ScalarUDFImpl for DateTruncFunc {
&self.signature
}
+ // keep return_type implementation for information schema generation
Review Comment:
This seems like a bug
##########
datafusion/spark/src/function/datetime/date_trunc.rs:
##########
@@ -0,0 +1,168 @@
+// 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.
+
+use std::any::Any;
+use std::sync::Arc;
+
+use arrow::datatypes::{DataType, Field, FieldRef, TimeUnit};
+use datafusion_common::types::{NativeType, logical_string};
+use datafusion_common::utils::take_function_args;
+use datafusion_common::{Result, ScalarValue, internal_err, plan_err};
+use datafusion_expr::expr::ScalarFunction;
+use datafusion_expr::simplify::{ExprSimplifyResult, SimplifyContext};
+use datafusion_expr::{
+ Coercion, ColumnarValue, Expr, ExprSchemable, ReturnFieldArgs,
ScalarFunctionArgs,
+ ScalarUDFImpl, Signature, TypeSignatureClass, Volatility,
+};
+
+/// Spark date_trunc supports extra format aliases.
+/// It also handles timestamps with timezones by converting to session
timezone first.
+/// <https://spark.apache.org/docs/latest/api/sql/index.html#date_trunc>
+#[derive(Debug, PartialEq, Eq, Hash)]
+pub struct SparkDateTrunc {
+ signature: Signature,
+}
+
+impl Default for SparkDateTrunc {
+ fn default() -> Self {
+ Self::new()
+ }
+}
+
+impl SparkDateTrunc {
+ pub fn new() -> Self {
+ Self {
+ signature: Signature::coercible(
+ vec![
+
Coercion::new_exact(TypeSignatureClass::Native(logical_string())),
+ Coercion::new_implicit(
+ TypeSignatureClass::Timestamp,
+ vec![TypeSignatureClass::Native(logical_string())],
+ NativeType::Timestamp(TimeUnit::Microsecond, None),
+ ),
+ ],
+ Volatility::Immutable,
+ ),
+ }
+ }
+}
+
+impl ScalarUDFImpl for SparkDateTrunc {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn name(&self) -> &str {
+ "date_trunc"
+ }
+
+ fn signature(&self) -> &Signature {
+ &self.signature
+ }
+
+ fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
+ internal_err!("return_field_from_args should be used instead")
+ }
+
+ fn return_field_from_args(&self, args: ReturnFieldArgs) ->
Result<FieldRef> {
+ let nullable = args.arg_fields.iter().any(|f| f.is_nullable());
+
+ Ok(Arc::new(Field::new(
+ self.name(),
+ args.arg_fields[1].data_type().clone(),
+ nullable,
+ )))
+ }
+
+ fn invoke_with_args(&self, _args: ScalarFunctionArgs) ->
Result<ColumnarValue> {
+ internal_err!(
+ "spark date_trunc should have been simplified to standard
date_trunc"
+ )
+ }
+
+ fn simplify(
+ &self,
+ args: Vec<Expr>,
+ info: &SimplifyContext,
+ ) -> Result<ExprSimplifyResult> {
+ let [fmt_expr, ts_expr] = take_function_args(self.name(), args)?;
+
+ let fmt = match fmt_expr.as_literal() {
+ Some(ScalarValue::Utf8(Some(v)))
+ | Some(ScalarValue::Utf8View(Some(v)))
+ | Some(ScalarValue::LargeUtf8(Some(v))) => v.to_lowercase(),
+ _ => {
+ return plan_err!(
+ "First argument of `DATE_TRUNC` must be non-null scalar
Utf8"
+ );
+ }
+ };
+
+ // Map Spark-specific fmt aliases to datafusion ones
+ let fmt = match fmt.as_str() {
+ "yy" | "yyyy" => "year",
+ "mm" | "mon" => "month",
+ "dd" => "day",
+ other => other,
+ };
+
+ let session_tz = info.config_options().execution.time_zone.clone();
+ let ts_type = ts_expr.get_type(info.schema())?;
+
+ // Spark interprets timestamps in the session timezone before
truncating,
+ // then returns a timestamp at microsecond precision.
+ // See:
https://github.com/apache/spark/blob/f310f4fcc95580a6824bc7d22b76006f79b8804a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala#L492
+ //
+ // For sub-second truncations (second, millisecond, microsecond),
timezone
+ // adjustment is unnecessary since timezone offsets are whole seconds.
+ let ts_expr = match (&ts_type, fmt) {
+ // Sub-second truncations don't need timezone adjustment
+ (_, "second" | "millisecond" | "microsecond") => ts_expr,
+
+ // Timestamp with timezone: convert to session timezone, strip
timezone and convert back to original timezone
+ (DataType::Timestamp(unit, tz), _) => {
+ let ts_expr = match &session_tz {
+ Some(session_tz) => ts_expr.cast_to(
+ &DataType::Timestamp(
+ TimeUnit::Microsecond,
+ Some(Arc::from(session_tz.as_str())),
+ ),
+ info.schema(),
+ )?,
+ None => ts_expr,
+ };
+ Expr::ScalarFunction(ScalarFunction::new_udf(
+ datafusion_functions::datetime::to_local_time(),
+ vec![ts_expr],
+ ))
+ .cast_to(&DataType::Timestamp(*unit, tz.clone()),
info.schema())?
+ }
+
+ // Timestamp without timezone: use as-is
+ _ => ts_expr,
Review Comment:
The above arm catches all timestamps though? Since it doesn't match on
`Some(tz)`; so when would this arm take effect?
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