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// 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 arrow_array::{
cast::as_primitive_array,
types::{Int32Type, TimestampMicrosecondType},
};
use arrow_schema::{ArrowError, DataType};
use std::any::Any;
use std::sync::Arc;
use crate::timezone::Tz;
use arrow::{
array::{as_dictionary_array, Array, ArrayRef, PrimitiveArray},
temporal_conversions::as_datetime,
};
use chrono::{DateTime, Offset, TimeZone};
use datafusion_physical_plan::PhysicalExpr;
/// A utility function from DataFusion. It is not exposed by DataFusion.
pub fn down_cast_any_ref(any: &dyn Any) -> &dyn Any {
if any.is::<Arc<dyn PhysicalExpr>>() {
any.downcast_ref::<Arc<dyn PhysicalExpr>>()
.unwrap()
.as_any()
} else if any.is::<Box<dyn PhysicalExpr>>() {
any.downcast_ref::<Box<dyn PhysicalExpr>>()
.unwrap()
.as_any()
} else {
any
}
}
/// Preprocesses input arrays to add timezone information from Spark to Arrow array datatype or
/// to apply timezone offset.
//
// We consider the following cases:
//
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Conversion | Input array | Timezone | Output array |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Timestamp -> | Array in UTC | Timezone of input | A timestamp with the timezone |
// | Utf8 or Date32 | | | offset applied and timezone |
// | | | | removed |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Timestamp -> | Array in UTC | Timezone of input | Same as input array |
// | Timestamp w/Timezone| | | |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Timestamp_ntz -> | Array in | Timezone of input | Same as input array |
// | Utf8 or Date32 | timezone | | |
// | | session local| | |
// | | timezone | | |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Timestamp_ntz -> | Array in | Timezone of input | Array in UTC and timezone |
// | Timestamp w/Timezone | session local| | specified in input |
// | | timezone | | |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
// | Timestamp(_ntz) -> | |
// | Any other type | Not Supported |
// | --------------------- | ------------ | ----------------- | -------------------------------- |
//
pub fn array_with_timezone(
array: ArrayRef,
timezone: String,
to_type: Option<&DataType>,
) -> Result<ArrayRef, ArrowError> {
match array.data_type() {
DataType::Timestamp(_, None) => {
assert!(!timezone.is_empty());
match to_type {
Some(DataType::Utf8) | Some(DataType::Date32) => Ok(array),
Some(DataType::Timestamp(_, Some(_))) => {
timestamp_ntz_to_timestamp(array, timezone.as_str(), Some(timezone.as_str()))
}
_ => {
// Not supported
panic!(
"Cannot convert from {:?} to {:?}",
array.data_type(),
to_type.unwrap()
)
}
}
}
DataType::Timestamp(_, Some(_)) => {
assert!(!timezone.is_empty());
let array = as_primitive_array::<TimestampMicrosecondType>(&array);
let array_with_timezone = array.clone().with_timezone(timezone.clone());
let array = Arc::new(array_with_timezone) as ArrayRef;
match to_type {
Some(DataType::Utf8) | Some(DataType::Date32) => {
pre_timestamp_cast(array, timezone)
}
_ => Ok(array),
}
}
DataType::Dictionary(_, value_type)
if matches!(value_type.as_ref(), &DataType::Timestamp(_, _)) =>
{
let dict = as_dictionary_array::<Int32Type>(&array);
let array = as_primitive_array::<TimestampMicrosecondType>(dict.values());
let array_with_timezone =
array_with_timezone(Arc::new(array.clone()) as ArrayRef, timezone, to_type)?;
let dict = dict.with_values(array_with_timezone);
Ok(Arc::new(dict))
}
_ => Ok(array),
}
}
fn datetime_cast_err(value: i64) -> ArrowError {
ArrowError::CastError(format!(
"Cannot convert TimestampMicrosecondType {value} to datetime. Comet only supports dates between Jan 1, 262145 BCE and Dec 31, 262143 CE",
))
}
/// Takes in a Timestamp(Microsecond, None) array and a timezone id, and returns
/// a Timestamp(Microsecond, Some<_>) array.
/// The understanding is that the input array has time in the timezone specified in the second
/// argument.
/// Parameters:
/// array - input array of timestamp without timezone
/// tz - timezone of the values in the input array
/// to_timezone - timezone to change the input values to
fn timestamp_ntz_to_timestamp(
array: ArrayRef,
tz: &str,
to_timezone: Option<&str>,
) -> Result<ArrayRef, ArrowError> {
assert!(!tz.is_empty());
match array.data_type() {
DataType::Timestamp(_, None) => {
let array = as_primitive_array::<TimestampMicrosecondType>(&array);
let tz: Tz = tz.parse()?;
let array: PrimitiveArray<TimestampMicrosecondType> = array.try_unary(|value| {
as_datetime::<TimestampMicrosecondType>(value)
.ok_or_else(|| datetime_cast_err(value))
.map(|local_datetime| {
let datetime: DateTime<Tz> =
tz.from_local_datetime(&local_datetime).unwrap();
datetime.timestamp_micros()
})
})?;
let array_with_tz = if let Some(to_tz) = to_timezone {
array.with_timezone(to_tz)
} else {
array
};
Ok(Arc::new(array_with_tz))
}
_ => Ok(array),
}
}
/// This takes for special pre-casting cases of Spark. E.g., Timestamp to String.
fn pre_timestamp_cast(array: ArrayRef, timezone: String) -> Result<ArrayRef, ArrowError> {
assert!(!timezone.is_empty());
match array.data_type() {
DataType::Timestamp(_, _) => {
// Spark doesn't output timezone while casting timestamp to string, but arrow's cast
// kernel does if timezone exists. So we need to apply offset of timezone to array
// timestamp value and remove timezone from array datatype.
let array = as_primitive_array::<TimestampMicrosecondType>(&array);
let tz: Tz = timezone.parse()?;
let array: PrimitiveArray<TimestampMicrosecondType> = array.try_unary(|value| {
as_datetime::<TimestampMicrosecondType>(value)
.ok_or_else(|| datetime_cast_err(value))
.map(|datetime| {
let offset = tz.offset_from_utc_datetime(&datetime).fix();
let datetime = datetime + offset;
datetime.and_utc().timestamp_micros()
})
})?;
Ok(Arc::new(array))
}
_ => Ok(array),
}
}