[GitHub] [arrow-datafusion] liukun4515 commented on a change in pull request #1946: Add examples to use MemTable and TableProvider (#1864)

[GitBox <gi...@apache.org>]

liukun4515 commented on a change in pull request #1946:
URL: https://github.com/apache/arrow-datafusion/pull/1946#discussion_r821428444



##########
File path: datafusion-examples/examples/memtable.rs
##########
@@ -0,0 +1,82 @@
+// 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::{UInt64Builder, UInt8Builder};
+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::ExecutionContext;
+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 mut ctx = ExecutionContext::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.get(0).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 mut id_array = UInt8Builder::new(1);

Review comment:
       It's better to use below api to create Array
   ```
   let array : defile_type = [Some(1), Some(2)].into_iter().collect();
   ```




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