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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 datafusion::arrow::datatypes::{DataType, Field, Schema};
use datafusion::error::Result;
use datafusion::prelude::*;
use std::fs;
/// This example demonstrates executing a simple query against an Arrow data source (Parquet) and
/// fetching results, using the DataFrame trait
#[tokio::main]
async fn main() -> Result<()> {
// create local execution context
let ctx = SessionContext::new();
let testdata = datafusion::test_util::parquet_test_data();
let filename = &format!("{testdata}/alltypes_plain.parquet");
// define the query using the DataFrame trait
let df = ctx
.read_parquet(filename, ParquetReadOptions::default())
.await?
.select_columns(&["id", "bool_col", "timestamp_col"])?
.filter(col("id").gt(lit(1)))?;
// print the results
df.show().await?;
// Reading CSV file with inferred schema example
let csv_df = example_read_csv_file_with_inferred_schema().await;
csv_df.show().await?;
// Reading CSV file with defined schema
let csv_df = example_read_csv_file_with_schema().await;
csv_df.show().await?;
Ok(())
}
// Function to create an test CSV file
fn create_csv_file(path: String) {
// Create the data to put into the csv file with headers
let content = r#"id,time,vote,unixtime,rating
a1,"10 6, 2013",3,1381017600,5.0
a2,"08 9, 2013",2,1376006400,4.5"#;
// write the data
fs::write(path, content).expect("Problem with writing file!");
}
// Example to read data from a csv file with inferred schema
async fn example_read_csv_file_with_inferred_schema() -> DataFrame {
let path = "example.csv";
// Create a csv file using the predefined function
create_csv_file(path.to_string());
// Create a session context
let ctx = SessionContext::new();
// Register a lazy DataFrame using the context
ctx.read_csv(path, CsvReadOptions::default()).await.unwrap()
}
// Example to read csv file with a defined schema for the csv file
async fn example_read_csv_file_with_schema() -> DataFrame {
let path = "example.csv";
// Create a csv file using the predefined function
create_csv_file(path.to_string());
// Create a session context
let ctx = SessionContext::new();
// Define the schema
let schema = Schema::new(vec![
Field::new("id", DataType::Utf8, false),
Field::new("time", DataType::Utf8, false),
Field::new("vote", DataType::Int32, true),
Field::new("unixtime", DataType::Int64, false),
Field::new("rating", DataType::Float32, true),
]);
// Create a csv option provider with the desired schema
let csv_read_option = CsvReadOptions {
// Update the option provider with the defined schema
schema: Some(&schema),
..Default::default()
};
// Register a lazy DataFrame by using the context and option provider
ctx.read_csv(path, csv_read_option).await.unwrap()
}