Arrow CSV reader and filtering

Cargo.toml

@@ -4,4 +4,6 @@ version = "0.1.0"
 edition = "2021"
 
 [dependencies]
-arrow = "52.0.0"
+arrow = "52.0.0"
+arrow-schema = "52.0.0"
+arrow-csv = "52.0.0"

data/employee.csv

@@ -0,0 +1,5 @@
+id,first_name,last_name,state,job_title,salary
+1,Bill,Hopkins,CA,Manager,12000
+2,Gregg,Langford,CO,Driver,10000
+3,John,Travis,CO,"Manager, Software",11500
+4,Von,Mill,,Defensive End,11500

src/main.rs

@@ -1,12 +1,59 @@
+use std::fs::File;
+use std::path::Path;
+use std::sync::Arc;
+
 use arrow::array::Int32Array;
+use arrow_csv::ReaderBuilder;
+// use arrow::csv::ReaderBuilder;
+// use arrow::datatypes::{DataType, Field, Schema};
+use arrow_schema::*;
 use rust_query::arrow_types;
 
 // Use our rust-query library
 fn main() {
-
     let a = Int32Array::from(vec![10]);
     let b = arrow_types::Int8Type::from(vec![10]);
 
     println!("{:?}", a);
     println!("{:?}", b);
-}
+
+    // Code for the query `SELECT * FROM employee WHERE state = 'CO'`
+    // against a CSV file containing the columns `id`, `first_name`,
+    // `last_name`, `state`, `job_title`, and `salary`
+    let schema = Schema::new(vec![
+        Field::new("id", DataType::Int8, false),
+        Field::new("first_name", DataType::Utf8, false),
+        Field::new("last_name", DataType::Utf8, false),
+        Field::new("state", DataType::Utf8, true),
+        Field::new("job_title", DataType::Utf8, false),
+        Field::new("salary", DataType::Int16, false),
+    ]);
+
+    let path = Path::new("/Users/gabestechschulte/Documents/repos/rust-query/data/employee.csv");
+    let display = path.display();
+    let file = match File::open(&path) {
+        Err(why) => panic!("Could not read {}: {}", display, why),
+        Ok(file) => file,
+    };
+
+    let mut batch = ReaderBuilder::new(Arc::new(schema))
+        .with_header(true)
+        .build(file)
+        .unwrap();
+    let batch_reader = batch.next().unwrap().unwrap();
+
+    assert_eq!(batch_reader.num_rows(), 4);
+    assert_eq!(batch_reader.num_columns(), 6);
+
+    let col_by_idx = batch_reader.column(2);
+    let col_by_name = batch_reader.column_by_name("first_name");
+
+    println!("{:?}", col_by_name);
+
+    for idx in 0..batch_reader.num_columns() {
+        let arr = batch_reader.column(idx).as_ref();
+
+        // Apply filter using compute kernel
+        // let filtered = filter
+    }
+}