| // 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() |
| } |