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support to_timestamp with optional chrono formats (#8886)
* Support to_timestamp with chrono formatting #5398 * Updated user guide's to_timestamp to include chrono formatting information #5398 * Minor comment update. * Small documentation updates for to_timestamp functions. * Cargo fmt and clippy improvements. * Switched to assert and unwrap_err based on feedback * Fixed assert, code compiles and runs as expected now. * Fix fmt (again). * Add additional to_timestamp tests covering usage with tables with and without valid formats. * to_timestamp documentation fixes. * - Changed internal_err! -> exec_err! for unsupported data type errors. - Extracted out to_timestamp_impl method to reduce code duplication as per PR feedback. - Extracted out validate_to_timestamp_data_types to reduce code duplication as per PR feedback. - Added additional tests for argument validation and invalid arguments. - Removed unnecessary shim function 'string_to_timestamp_nanos_with_format_shim' * Resolved merge conflict, updated toStringXXX methods to reflect upstream change * prettier * Fix clippy --------- Co-authored-by: Andrew Lamb <[email protected]>
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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. | ||
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| use std::sync::Arc; | ||
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| use datafusion::arrow::array::StringArray; | ||
| use datafusion::arrow::datatypes::{DataType, Field, Schema}; | ||
| use datafusion::arrow::record_batch::RecordBatch; | ||
| use datafusion::error::Result; | ||
| use datafusion::prelude::*; | ||
| use datafusion_common::assert_contains; | ||
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| /// This example demonstrates how to use the to_timestamp function in the DataFrame API as well as via sql. | ||
| #[tokio::main] | ||
| async fn main() -> Result<()> { | ||
| // define a schema. | ||
| let schema = Arc::new(Schema::new(vec![ | ||
| Field::new("a", DataType::Utf8, false), | ||
| Field::new("b", DataType::Utf8, false), | ||
| ])); | ||
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| // define data. | ||
| let batch = RecordBatch::try_new( | ||
| schema, | ||
| vec![ | ||
| Arc::new(StringArray::from(vec![ | ||
| "2020-09-08T13:42:29Z", | ||
| "2020-09-08T13:42:29.190855-05:00", | ||
| "2020-08-09 12:13:29", | ||
| "2020-01-02", | ||
| ])), | ||
| Arc::new(StringArray::from(vec![ | ||
| "2020-09-08T13:42:29Z", | ||
| "2020-09-08T13:42:29.190855-05:00", | ||
| "08-09-2020 13/42/29", | ||
| "09-27-2020 13:42:29-05:30", | ||
| ])), | ||
| ], | ||
| )?; | ||
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| // declare a new context. In spark API, this corresponds to a new spark SQLsession | ||
| let ctx = SessionContext::new(); | ||
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| // declare a table in memory. In spark API, this corresponds to createDataFrame(...). | ||
| ctx.register_batch("t", batch)?; | ||
| let df = ctx.table("t").await?; | ||
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| // use to_timestamp function to convert col 'a' to timestamp type using the default parsing | ||
| let df = df.with_column("a", to_timestamp(vec![col("a")]))?; | ||
| // use to_timestamp_seconds function to convert col 'b' to timestamp(Seconds) type using a list of chrono formats to try | ||
| let df = df.with_column( | ||
| "b", | ||
| to_timestamp_seconds(vec![ | ||
| col("b"), | ||
| lit("%+"), | ||
| lit("%d-%m-%Y %H/%M/%S"), | ||
| lit("%m-%d-%Y %H:%M:%S%#z"), | ||
| ]), | ||
| )?; | ||
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| let df = df.select_columns(&["a", "b"])?; | ||
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| // print the results | ||
| df.show().await?; | ||
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| // use sql to convert col 'a' to timestamp using the default parsing | ||
| let df = ctx.sql("select to_timestamp(a) from t").await?; | ||
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| // print the results | ||
| df.show().await?; | ||
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| // use sql to convert col 'b' to timestamp using a list of chrono formats to try | ||
| let df = ctx.sql("select to_timestamp(b, '%+', '%d-%m-%Y %H/%M/%S', '%m-%d-%Y %H:%M:%S%#z') from t").await?; | ||
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| // print the results | ||
| df.show().await?; | ||
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| // use sql to convert a static string to a timestamp using a list of chrono formats to try | ||
| let df = ctx.sql("select to_timestamp('01-14-2023 01:01:30+05:30', '%+', '%d-%m-%Y %H/%M/%S', '%m-%d-%Y %H:%M:%S%#z')").await?; | ||
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| // print the results | ||
| df.show().await?; | ||
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| // use sql to convert a static string to a timestamp using a non-matching chrono format to try | ||
| let result = ctx | ||
| .sql("select to_timestamp('01-14-2023 01/01/30', '%d-%m-%Y %H:%M:%S')") | ||
| .await? | ||
| .collect() | ||
| .await; | ||
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| let expected = "Error parsing timestamp from '01-14-2023 01/01/30' using format '%d-%m-%Y %H:%M:%S': input contains invalid characters"; | ||
| assert_contains!(result.unwrap_err().to_string(), expected); | ||
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| Ok(()) | ||
| } |
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