DynamoDB examples using SDK for Rust

pub async fn create_table(
    client: &Client,
    table: &str,
    key: &str,
) -> Result<CreateTableOutput, Error> {
    let a_name: String = key.into();
    let table_name: String = table.into();

    let ad = AttributeDefinition::builder()
        .attribute_name(&a_name)
        .attribute_type(ScalarAttributeType::S)
        .build()
        .map_err(Error::BuildError)?;

    let ks = KeySchemaElement::builder()
        .attribute_name(&a_name)
        .key_type(KeyType::Hash)
        .build()
        .map_err(Error::BuildError)?;

    let pt = ProvisionedThroughput::builder()
        .read_capacity_units(10)
        .write_capacity_units(5)
        .build()
        .map_err(Error::BuildError)?;

    let create_table_response = client
        .create_table()
        .table_name(table_name)
        .key_schema(ks)
        .attribute_definitions(ad)
        .provisioned_throughput(pt)
        .send()
        .await;

    match create_table_response {
        Ok(out) => {
            println!("Added table {} with key {}", table, key);
            Ok(out)
        }
        Err(e) => {
            eprintln!("Got an error creating table:");
            eprintln!("{}", e);
            Err(Error::unhandled(e))
        }
    }
}

pub async fn delete_item(
    client: &Client,
    table: &str,
    key: &str,
    value: &str,
) -> Result<DeleteItemOutput, Error> {
    match client
        .delete_item()
        .table_name(table)
        .key(key, AttributeValue::S(value.into()))
        .send()
        .await
    {
        Ok(out) => {
            println!("Deleted item from table");
            Ok(out)
        }
        Err(e) => Err(Error::unhandled(e)),
    }
}

pub async fn delete_table(client: &Client, table: &str) -> Result<DeleteTableOutput, Error> {
    let resp = client.delete_table().table_name(table).send().await;

    match resp {
        Ok(out) => {
            println!("Deleted table");
            Ok(out)
        }
        Err(e) => Err(Error::Unhandled(e.into())),
    }
}

pub async fn list_tables(client: &Client) -> Result<Vec<String>, Error> {
    let paginator = client.list_tables().into_paginator().items().send();
    let table_names = paginator.collect::<Result<Vec<_>, _>>().await?;

    println!("Tables:");

    for name in &table_names {
        println!("  {}", name);
    }

    println!("Found {} tables", table_names.len());
    Ok(table_names)
}

Determine whether table exists.

pub async fn table_exists(client: &Client, table: &str) -> Result<bool, Error> {
    debug!("Checking for table: {table}");
    let table_list = client.list_tables().send().await;

    match table_list {
        Ok(list) => Ok(list.table_names().contains(&table.into())),
        Err(e) => Err(e.into()),
    }
}

pub async fn add_item(client: &Client, item: Item, table: &String) -> Result<ItemOut, Error> {
    let user_av = AttributeValue::S(item.username);
    let type_av = AttributeValue::S(item.p_type);
    let age_av = AttributeValue::S(item.age);
    let first_av = AttributeValue::S(item.first);
    let last_av = AttributeValue::S(item.last);

    let request = client
        .put_item()
        .table_name(table)
        .item("username", user_av)
        .item("account_type", type_av)
        .item("age", age_av)
        .item("first_name", first_av)
        .item("last_name", last_av);

    println!("Executing request [{request:?}] to add item...");

    let resp = request.send().await?;

    let attributes = resp.attributes().unwrap();

    let username = attributes.get("username").cloned();
    let first_name = attributes.get("first_name").cloned();
    let last_name = attributes.get("last_name").cloned();
    let age = attributes.get("age").cloned();
    let p_type = attributes.get("p_type").cloned();

    println!(
        "Added user {:?}, {:?} {:?}, age {:?} as {:?} user",
        username, first_name, last_name, age, p_type
    );

    Ok(ItemOut {
        p_type,
        age,
        username,
        first_name,
        last_name,
    })
}

Find the movies made in the specified year.

pub async fn movies_in_year(
    client: &Client,
    table_name: &str,
    year: u16,
) -> Result<Vec<Movie>, MovieError> {
    let results = client
        .query()
        .table_name(table_name)
        .key_condition_expression("#yr = :yyyy")
        .expression_attribute_names("#yr", "year")
        .expression_attribute_values(":yyyy", AttributeValue::N(year.to_string()))
        .send()
        .await?;

    if let Some(items) = results.items {
        let movies = items.iter().map(|v| v.into()).collect();
        Ok(movies)
    } else {
        Ok(vec![])
    }
}

pub async fn list_items(client: &Client, table: &str, page_size: Option<i32>) -> Result<(), Error> {
    let page_size = page_size.unwrap_or(10);
    let items: Result<Vec<_>, _> = client
        .scan()
        .table_name(table)
        .limit(page_size)
        .into_paginator()
        .items()
        .send()
        .collect()
        .await;

    println!("Items in table (up to {page_size}):");
    for item in items? {
        println!("   {:?}", item);
    }

    Ok(())
}

/// Lists your tables from a local DynamoDB instance by setting the SDK Config's
/// endpoint_url and test_credentials.
#[tokio::main]
async fn main() {
    tracing_subscriber::fmt::init();

    let config = aws_config::defaults(aws_config::BehaviorVersion::latest())
        .test_credentials()
        // DynamoDB run locally uses port 8000 by default.
        .endpoint_url("http://localhost:8000")
        .load()
        .await;
    let dynamodb_local_config = aws_sdk_dynamodb::config::Builder::from(&config).build();

    let client = aws_sdk_dynamodb::Client::from_conf(dynamodb_local_config);

    let list_resp = client.list_tables().send().await;
    match list_resp {
        Ok(resp) => {
            println!("Found {} tables", resp.table_names().len());
            for name in resp.table_names() {
                println!("  {}", name);
            }
        }
        Err(err) => eprintln!("Failed to list local dynamodb tables: {err:?}"),
    }
}

Shows how to develop a photo asset management application that detects labels in images using Amazon Rekognition and stores them for later retrieval.

For complete source code and instructions on how to set up and run, see the full example on GitHub.

For a deep dive into the origin of this example see the post on AWS Community.

async fn make_table(
    client: &Client,
    table: &str,
    key: &str,
) -> Result<(), SdkError<CreateTableError>> {
    let ad = AttributeDefinition::builder()
        .attribute_name(key)
        .attribute_type(ScalarAttributeType::S)
        .build()
        .expect("creating AttributeDefinition");

    let ks = KeySchemaElement::builder()
        .attribute_name(key)
        .key_type(KeyType::Hash)
        .build()
        .expect("creating KeySchemaElement");

    let pt = ProvisionedThroughput::builder()
        .read_capacity_units(10)
        .write_capacity_units(5)
        .build()
        .expect("creating ProvisionedThroughput");

    match client
        .create_table()
        .table_name(table)
        .key_schema(ks)
        .attribute_definitions(ad)
        .provisioned_throughput(pt)
        .send()
        .await
    {
        Ok(_) => Ok(()),
        Err(e) => Err(e),
    }
}

async fn add_item(client: &Client, item: Item) -> Result<(), SdkError<ExecuteStatementError>> {
    match client
        .execute_statement()
        .statement(format!(
            r#"INSERT INTO "{}" VALUE {{
                "{}": ?,
                "acount_type": ?,
                "age": ?,
                "first_name": ?,
                "last_name": ?
        }} "#,
            item.table, item.key
        ))
        .set_parameters(Some(vec![
            AttributeValue::S(item.utype),
            AttributeValue::S(item.age),
            AttributeValue::S(item.first_name),
            AttributeValue::S(item.last_name),
        ]))
        .send()
        .await
    {
        Ok(_) => Ok(()),
        Err(e) => Err(e),
    }
}

async fn query_item(client: &Client, item: Item) -> bool {
    match client
        .execute_statement()
        .statement(format!(
            r#"SELECT * FROM "{}" WHERE "{}" = ?"#,
            item.table, item.key
        ))
        .set_parameters(Some(vec![AttributeValue::S(item.value)]))
        .send()
        .await
    {
        Ok(resp) => {
            if !resp.items().is_empty() {
                println!("Found a matching entry in the table:");
                println!("{:?}", resp.items.unwrap_or_default().pop());
                true
            } else {
                println!("Did not find a match.");
                false
            }
        }
        Err(e) => {
            println!("Got an error querying table:");
            println!("{}", e);
            process::exit(1);
        }
    }
}

async fn remove_item(client: &Client, table: &str, key: &str, value: String) -> Result<(), Error> {
    client
        .execute_statement()
        .statement(format!(r#"DELETE FROM "{table}" WHERE "{key}" = ?"#))
        .set_parameters(Some(vec![AttributeValue::S(value)]))
        .send()
        .await?;

    println!("Deleted item.");

    Ok(())
}

async fn remove_table(client: &Client, table: &str) -> Result<(), Error> {
    client.delete_table().table_name(table).send().await?;

    Ok(())
}

Get EXIF information from a JPG, JPEG, or PNG file, upload the image file to an Amazon S3 bucket, use Amazon Rekognition to identify the three top attributes (labels in Amazon Rekognition) in the file, and add the EXIF and label information to a Amazon DynamoDB table in the Region.

For complete source code and instructions on how to set up and run, see the full example on GitHub.

Consuming a DynamoDB event with Lambda using Rust.

use lambda_runtime::{service_fn, tracing, Error, LambdaEvent};
use aws_lambda_events::{
    event::dynamodb::{Event, EventRecord},
   };


// Built with the following dependencies:
//lambda_runtime = "0.11.1"
//serde_json = "1.0"
//tokio = { version = "1", features = ["macros"] }
//tracing = { version = "0.1", features = ["log"] }
//tracing-subscriber = { version = "0.3", default-features = false, features = ["fmt"] }
//aws_lambda_events = "0.15.0"

async fn function_handler(event: LambdaEvent<Event>) ->Result<(), Error> {
    
    let records = &event.payload.records;
    tracing::info!("event payload: {:?}",records);
    if records.is_empty() {
        tracing::info!("No records found. Exiting.");
        return Ok(());
    }

    for record in records{
        log_dynamo_dbrecord(record);
    }

    tracing::info!("Dynamo db records processed");

    // Prepare the response
    Ok(())

}

fn log_dynamo_dbrecord(record: &EventRecord)-> Result<(), Error>{
    tracing::info!("EventId: {}", record.event_id);
    tracing::info!("EventName: {}", record.event_name);
    tracing::info!("DynamoDB Record: {:?}", record.change );
    Ok(())

}

#[tokio::main]
async fn main() -> Result<(), Error> {
    tracing_subscriber::fmt()
    .with_max_level(tracing::Level::INFO)
    .with_target(false)
    .without_time()
    .init();

    let func = service_fn(function_handler);
    lambda_runtime::run(func).await?;
    Ok(())
    
}

Reporting DynamoDB batch item failures with Lambda using Rust.

use aws_lambda_events::{
    event::dynamodb::{Event, EventRecord, StreamRecord},
    streams::{DynamoDbBatchItemFailure, DynamoDbEventResponse},
};
use lambda_runtime::{run, service_fn, Error, LambdaEvent};

/// Process the stream record
fn process_record(record: &EventRecord) -> Result<(), Error> {
    let stream_record: &StreamRecord = &record.change;

    // process your stream record here...
    tracing::info!("Data: {:?}", stream_record);

    Ok(())
}

/// Main Lambda handler here...
async fn function_handler(event: LambdaEvent<Event>) -> Result<DynamoDbEventResponse, Error> {
    let mut response = DynamoDbEventResponse {
        batch_item_failures: vec![],
    };

    let records = &event.payload.records;

    if records.is_empty() {
        tracing::info!("No records found. Exiting.");
        return Ok(response);
    }

    for record in records {
        tracing::info!("EventId: {}", record.event_id);

        // Couldn't find a sequence number
        if record.change.sequence_number.is_none() {
            response.batch_item_failures.push(DynamoDbBatchItemFailure {
                item_identifier: Some("".to_string()),
            });
            return Ok(response);
        }

        // Process your record here...
        if process_record(record).is_err() {
            response.batch_item_failures.push(DynamoDbBatchItemFailure {
                item_identifier: record.change.sequence_number.clone(),
            });
            /* Since we are working with streams, we can return the failed item immediately.
            Lambda will immediately begin to retry processing from this failed item onwards. */
            return Ok(response);
        }
    }

    tracing::info!("Successfully processed {} record(s)", records.len());

    Ok(response)
}

#[tokio::main]
async fn main() -> Result<(), Error> {
    tracing_subscriber::fmt()
        .with_max_level(tracing::Level::INFO)
        // disable printing the name of the module in every log line.
        .with_target(false)
        // disabling time is handy because CloudWatch will add the ingestion time.
        .without_time()
        .init();

    run(service_fn(function_handler)).await
}