datafusion_functions/
lib.rs

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
// 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.
// Make cheap clones clear: https://github.com/apache/datafusion/issues/11143
#![deny(clippy::clone_on_ref_ptr)]

//! Function packages for [DataFusion].
//!
//! This crate contains a collection of various function packages for DataFusion,
//! implemented using the extension API. Users may wish to control which functions
//! are available to control the binary size of their application as well as
//! use dialect specific implementations of functions (e.g. Spark vs Postgres)
//!
//! Each package is implemented as a separate
//! module, activated by a feature flag.
//!
//! [DataFusion]: https://crates.io/crates/datafusion
//!
//! # Available Packages
//! See the list of [modules](#modules) in this crate for available packages.
//!
//! # Using A Package
//! You can register all functions in all packages using the [`register_all`] function.
//!
//! To access and use only the functions in a certain package, use the
//! `functions()` method in each module.
//!
//! ```
//! # fn main() -> datafusion_common::Result<()> {
//! # let mut registry = datafusion_execution::registry::MemoryFunctionRegistry::new();
//! # use datafusion_execution::FunctionRegistry;
//! // get the encoding functions
//! use datafusion_functions::encoding;
//! for udf in encoding::functions() {
//!   registry.register_udf(udf)?;
//! }
//! # Ok(())
//! # }
//! ```
//!
//! Each package also exports an `expr_fn` submodule to help create [`Expr`]s that invoke
//! functions using a fluent style. For example:
//!
//! ```
//! // create an Expr that will invoke the encode function
//! use datafusion_expr::{col, lit};
//! use datafusion_functions::expr_fn;
//! // Equivalent to "encode(my_data, 'hex')" in SQL:
//! let expr = expr_fn::encode(col("my_data"), lit("hex"));
//! ```
//!
//![`Expr`]: datafusion_expr::Expr
//!
//! # Implementing A New Package
//!
//! To add a new package to this crate, you should follow the model of existing
//! packages. The high level steps are:
//!
//! 1. Create a new module with the appropriate [`ScalarUDF`] implementations.
//!
//! 2. Use the macros in [`macros`] to create standard entry points.
//!
//! 3. Add a new feature to `Cargo.toml`, with any optional dependencies
//!
//! 4. Use the `make_package!` macro to expose the module when the
//!    feature is enabled.
//!
//! [`ScalarUDF`]: datafusion_expr::ScalarUDF
use datafusion_common::Result;
use datafusion_execution::FunctionRegistry;
use datafusion_expr::ScalarUDF;
use log::debug;
use std::sync::Arc;

#[macro_use]
pub mod macros;

#[cfg(feature = "string_expressions")]
pub mod string;
make_stub_package!(string, "string_expressions");

/// Core datafusion expressions
/// Enabled via feature flag `core_expressions`
#[cfg(feature = "core_expressions")]
pub mod core;
make_stub_package!(core, "core_expressions");

/// Date and time expressions.
/// Contains functions such as to_timestamp
/// Enabled via feature flag `datetime_expressions`
#[cfg(feature = "datetime_expressions")]
pub mod datetime;
make_stub_package!(datetime, "datetime_expressions");

/// Encoding expressions.
/// Contains Hex and binary `encode` and `decode` functions.
/// Enabled via feature flag `encoding_expressions`
#[cfg(feature = "encoding_expressions")]
pub mod encoding;
make_stub_package!(encoding, "encoding_expressions");

/// Mathematical functions.
/// Enabled via feature flag `math_expressions`
#[cfg(feature = "math_expressions")]
pub mod math;
make_stub_package!(math, "math_expressions");

/// Regular expression functions.
/// Enabled via feature flag `regex_expressions`
#[cfg(feature = "regex_expressions")]
pub mod regex;
make_stub_package!(regex, "regex_expressions");

#[cfg(feature = "crypto_expressions")]
pub mod crypto;
make_stub_package!(crypto, "crypto_expressions");

#[cfg(feature = "unicode_expressions")]
pub mod unicode;
make_stub_package!(unicode, "unicode_expressions");

#[cfg(any(feature = "datetime_expressions", feature = "unicode_expressions"))]
pub mod planner;

pub mod strings;

mod utils;

/// Fluent-style API for creating `Expr`s
pub mod expr_fn {
    #[cfg(feature = "core_expressions")]
    pub use super::core::expr_fn::*;
    #[cfg(feature = "crypto_expressions")]
    pub use super::crypto::expr_fn::*;
    #[cfg(feature = "datetime_expressions")]
    pub use super::datetime::expr_fn::*;
    #[cfg(feature = "encoding_expressions")]
    pub use super::encoding::expr_fn::*;
    #[cfg(feature = "math_expressions")]
    pub use super::math::expr_fn::*;
    #[cfg(feature = "regex_expressions")]
    pub use super::regex::expr_fn::*;
    #[cfg(feature = "string_expressions")]
    pub use super::string::expr_fn::*;
    #[cfg(feature = "unicode_expressions")]
    pub use super::unicode::expr_fn::*;
}

/// Return all default functions
pub fn all_default_functions() -> Vec<Arc<ScalarUDF>> {
    core::functions()
        .into_iter()
        .chain(datetime::functions())
        .chain(encoding::functions())
        .chain(math::functions())
        .chain(regex::functions())
        .chain(crypto::functions())
        .chain(unicode::functions())
        .chain(string::functions())
        .collect::<Vec<_>>()
}

/// Registers all enabled packages with a [`FunctionRegistry`]
pub fn register_all(registry: &mut dyn FunctionRegistry) -> Result<()> {
    let all_functions = all_default_functions();

    all_functions.into_iter().try_for_each(|udf| {
        let existing_udf = registry.register_udf(udf)?;
        if let Some(existing_udf) = existing_udf {
            debug!("Overwrite existing UDF: {}", existing_udf.name());
        }
        Ok(()) as Result<()>
    })?;
    Ok(())
}

#[cfg(test)]
mod tests {
    use crate::all_default_functions;
    use datafusion_common::Result;
    use std::collections::HashSet;

    #[test]
    fn test_no_duplicate_name() -> Result<()> {
        let mut names = HashSet::new();
        for func in all_default_functions() {
            assert!(
                names.insert(func.name().to_string().to_lowercase()),
                "duplicate function name: {}",
                func.name()
            );
            for alias in func.aliases() {
                assert!(
                    names.insert(alias.to_string().to_lowercase()),
                    "duplicate function name: {}",
                    alias
                );
            }
        }
        Ok(())
    }
}