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memtable.rs
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memtable.rs
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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::array::{UInt64Array, UInt8Array};
use datafusion::arrow::datatypes::{DataType, Field, Schema, SchemaRef};
use datafusion::arrow::record_batch::RecordBatch;
use datafusion::datasource::MemTable;
use datafusion::error::Result;
use datafusion::prelude::SessionContext;
use std::sync::Arc;
use std::time::Duration;
use tokio::time::timeout;
/// This example demonstrates executing a simple query against a Memtable
#[tokio::main]
async fn main() -> Result<()> {
let mem_table = create_memtable()?;
// create local execution context
let ctx = SessionContext::new();
// Register the in-memory table containing the data
ctx.register_table("users", Arc::new(mem_table))?;
let dataframe = ctx.sql("SELECT * FROM users;").await?;
timeout(Duration::from_secs(10), async move {
let result = dataframe.collect().await.unwrap();
let record_batch = result.first().unwrap();
assert_eq!(1, record_batch.column(0).len());
dbg!(record_batch.columns());
})
.await
.unwrap();
Ok(())
}
fn create_memtable() -> Result<MemTable> {
MemTable::try_new(get_schema(), vec![vec![create_record_batch()?]])
}
fn create_record_batch() -> Result<RecordBatch> {
let id_array = UInt8Array::from(vec![1]);
let account_array = UInt64Array::from(vec![9000]);
Ok(RecordBatch::try_new(
get_schema(),
vec![Arc::new(id_array), Arc::new(account_array)],
)
.unwrap())
}
fn get_schema() -> SchemaRef {
SchemaRef::new(Schema::new(vec![
Field::new("id", DataType::UInt8, false),
Field::new("bank_account", DataType::UInt64, true),
]))
}