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| 1 | +// Licensed to the Apache Software Foundation (ASF) under one |
| 2 | +// or more contributor license agreements. See the NOTICE file |
| 3 | +// distributed with this work for additional information |
| 4 | +// regarding copyright ownership. The ASF licenses this file |
| 5 | +// to you under the Apache License, Version 2.0 (the |
| 6 | +// "License"); you may not use this file except in compliance |
| 7 | +// with the License. You may obtain a copy of the License at |
| 8 | +// |
| 9 | +// http://www.apache.org/licenses/LICENSE-2.0 |
| 10 | +// |
| 11 | +// Unless required by applicable law or agreed to in writing, |
| 12 | +// software distributed under the License is distributed on an |
| 13 | +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| 14 | +// KIND, either express or implied. See the License for the |
| 15 | +// specific language governing permissions and limitations |
| 16 | +// under the License. |
| 17 | + |
| 18 | +use std::any::Any; |
| 19 | +use std::sync::Arc; |
| 20 | + |
| 21 | +use arrow::array::timezone::Tz; |
| 22 | +use arrow::array::{Array, ArrayRef, AsArray, PrimitiveBuilder, StringArrayType}; |
| 23 | +use arrow::datatypes::TimeUnit; |
| 24 | +use arrow::datatypes::{ |
| 25 | + ArrowTimestampType, DataType, Field, FieldRef, TimestampMicrosecondType, |
| 26 | + TimestampMillisecondType, TimestampNanosecondType, TimestampSecondType, |
| 27 | +}; |
| 28 | +use datafusion_common::types::{NativeType, logical_string}; |
| 29 | +use datafusion_common::utils::take_function_args; |
| 30 | +use datafusion_common::{Result, exec_datafusion_err, exec_err, internal_err}; |
| 31 | +use datafusion_expr::{ |
| 32 | + Coercion, ColumnarValue, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDFImpl, |
| 33 | + Signature, TypeSignatureClass, Volatility, |
| 34 | +}; |
| 35 | +use datafusion_functions::datetime::to_local_time::adjust_to_local_time; |
| 36 | +use datafusion_functions::utils::make_scalar_function; |
| 37 | + |
| 38 | +/// Apache Spark `from_utc_timestamp` function. |
| 39 | +/// |
| 40 | +/// Interprets the given timestamp as UTC and converts it to the given timezone. |
| 41 | +/// |
| 42 | +/// Timestamp in Apache Spark represents number of microseconds from the Unix epoch, which is not |
| 43 | +/// timezone-agnostic. So in Apache Spark this function just shift the timestamp value from UTC timezone to |
| 44 | +/// the given timezone. |
| 45 | +/// |
| 46 | +/// See <https://spark.apache.org/docs/latest/api/sql/index.html#from_utc_timestamp> |
| 47 | +#[derive(Debug, PartialEq, Eq, Hash)] |
| 48 | +pub struct SparkFromUtcTimestamp { |
| 49 | + signature: Signature, |
| 50 | +} |
| 51 | + |
| 52 | +impl Default for SparkFromUtcTimestamp { |
| 53 | + fn default() -> Self { |
| 54 | + Self::new() |
| 55 | + } |
| 56 | +} |
| 57 | + |
| 58 | +impl SparkFromUtcTimestamp { |
| 59 | + pub fn new() -> Self { |
| 60 | + Self { |
| 61 | + signature: Signature::coercible( |
| 62 | + vec![ |
| 63 | + Coercion::new_implicit( |
| 64 | + TypeSignatureClass::Timestamp, |
| 65 | + vec![TypeSignatureClass::Native(logical_string())], |
| 66 | + NativeType::Timestamp(TimeUnit::Microsecond, None), |
| 67 | + ), |
| 68 | + Coercion::new_exact(TypeSignatureClass::Native(logical_string())), |
| 69 | + ], |
| 70 | + Volatility::Immutable, |
| 71 | + ), |
| 72 | + } |
| 73 | + } |
| 74 | +} |
| 75 | + |
| 76 | +impl ScalarUDFImpl for SparkFromUtcTimestamp { |
| 77 | + fn as_any(&self) -> &dyn Any { |
| 78 | + self |
| 79 | + } |
| 80 | + |
| 81 | + fn name(&self) -> &str { |
| 82 | + "from_utc_timestamp" |
| 83 | + } |
| 84 | + |
| 85 | + fn signature(&self) -> &Signature { |
| 86 | + &self.signature |
| 87 | + } |
| 88 | + |
| 89 | + fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { |
| 90 | + internal_err!("return_field_from_args should be used instead") |
| 91 | + } |
| 92 | + |
| 93 | + fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> { |
| 94 | + let nullable = args.arg_fields.iter().any(|f| f.is_nullable()); |
| 95 | + |
| 96 | + Ok(Arc::new(Field::new( |
| 97 | + self.name(), |
| 98 | + args.arg_fields[0].data_type().clone(), |
| 99 | + nullable, |
| 100 | + ))) |
| 101 | + } |
| 102 | + |
| 103 | + fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { |
| 104 | + make_scalar_function(spark_from_utc_timestamp, vec![])(&args.args) |
| 105 | + } |
| 106 | +} |
| 107 | + |
| 108 | +fn spark_from_utc_timestamp(args: &[ArrayRef]) -> Result<ArrayRef> { |
| 109 | + let [timestamp, timezone] = take_function_args("from_utc_timestamp", args)?; |
| 110 | + |
| 111 | + match timestamp.data_type() { |
| 112 | + DataType::Timestamp(TimeUnit::Nanosecond, tz_opt) => { |
| 113 | + process_timestamp_with_tz_array::<TimestampNanosecondType>( |
| 114 | + timestamp, |
| 115 | + timezone, |
| 116 | + tz_opt.clone(), |
| 117 | + ) |
| 118 | + } |
| 119 | + DataType::Timestamp(TimeUnit::Microsecond, tz_opt) => { |
| 120 | + process_timestamp_with_tz_array::<TimestampMicrosecondType>( |
| 121 | + timestamp, |
| 122 | + timezone, |
| 123 | + tz_opt.clone(), |
| 124 | + ) |
| 125 | + } |
| 126 | + DataType::Timestamp(TimeUnit::Millisecond, tz_opt) => { |
| 127 | + process_timestamp_with_tz_array::<TimestampMillisecondType>( |
| 128 | + timestamp, |
| 129 | + timezone, |
| 130 | + tz_opt.clone(), |
| 131 | + ) |
| 132 | + } |
| 133 | + DataType::Timestamp(TimeUnit::Second, tz_opt) => { |
| 134 | + process_timestamp_with_tz_array::<TimestampSecondType>( |
| 135 | + timestamp, |
| 136 | + timezone, |
| 137 | + tz_opt.clone(), |
| 138 | + ) |
| 139 | + } |
| 140 | + ts_type => { |
| 141 | + exec_err!("`from_utc_timestamp`: unsupported argument types: {ts_type}") |
| 142 | + } |
| 143 | + } |
| 144 | +} |
| 145 | + |
| 146 | +fn process_timestamp_with_tz_array<T: ArrowTimestampType>( |
| 147 | + ts_array: &ArrayRef, |
| 148 | + tz_array: &ArrayRef, |
| 149 | + tz_opt: Option<Arc<str>>, |
| 150 | +) -> Result<ArrayRef> { |
| 151 | + match tz_array.data_type() { |
| 152 | + DataType::Utf8 => { |
| 153 | + process_arrays::<T, _>(tz_opt, ts_array, tz_array.as_string::<i32>()) |
| 154 | + } |
| 155 | + DataType::LargeUtf8 => { |
| 156 | + process_arrays::<T, _>(tz_opt, ts_array, tz_array.as_string::<i64>()) |
| 157 | + } |
| 158 | + DataType::Utf8View => { |
| 159 | + process_arrays::<T, _>(tz_opt, ts_array, tz_array.as_string_view()) |
| 160 | + } |
| 161 | + other => { |
| 162 | + exec_err!("`from_utc_timestamp`: timezone must be a string type, got {other}") |
| 163 | + } |
| 164 | + } |
| 165 | +} |
| 166 | + |
| 167 | +fn process_arrays<'a, T: ArrowTimestampType, S>( |
| 168 | + return_tz_opt: Option<Arc<str>>, |
| 169 | + ts_array: &ArrayRef, |
| 170 | + tz_array: &'a S, |
| 171 | +) -> Result<ArrayRef> |
| 172 | +where |
| 173 | + &'a S: StringArrayType<'a>, |
| 174 | +{ |
| 175 | + let ts_primitive = ts_array.as_primitive::<T>(); |
| 176 | + let mut builder = PrimitiveBuilder::<T>::with_capacity(ts_array.len()); |
| 177 | + |
| 178 | + for (ts_opt, tz_opt) in ts_primitive.iter().zip(tz_array.iter()) { |
| 179 | + match (ts_opt, tz_opt) { |
| 180 | + (Some(ts), Some(tz_str)) => { |
| 181 | + let tz: Tz = tz_str.parse().map_err(|e| { |
| 182 | + exec_datafusion_err!( |
| 183 | + "`from_utc_timestamp`: invalid timezone '{tz_str}': {e}" |
| 184 | + ) |
| 185 | + })?; |
| 186 | + let val = adjust_to_local_time::<T>(ts, tz)?; |
| 187 | + builder.append_value(val); |
| 188 | + } |
| 189 | + _ => builder.append_null(), |
| 190 | + } |
| 191 | + } |
| 192 | + |
| 193 | + builder = builder.with_timezone_opt(return_tz_opt); |
| 194 | + Ok(Arc::new(builder.finish())) |
| 195 | +} |
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