AWS SDK for JavaScript DataPipeline Client for Node.js, Browser and React Native.
AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data.
AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management.
AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.
To install the this package, simply type add or install @aws-sdk/client-data-pipeline using your favorite package manager:
npm install @aws-sdk/client-data-pipelineyarn add @aws-sdk/client-data-pipelinepnpm add @aws-sdk/client-data-pipeline
The AWS SDK is modulized by clients and commands.
To send a request, you only need to import the DataPipelineClient and
the commands you need, for example ListPipelinesCommand:
// ES5 example
const { DataPipelineClient, ListPipelinesCommand } = require("@aws-sdk/client-data-pipeline");// ES6+ example
import { DataPipelineClient, ListPipelinesCommand } from "@aws-sdk/client-data-pipeline";To send a request, you:
- Initiate client with configuration (e.g. credentials, region).
- Initiate command with input parameters.
- Call
sendoperation on client with command object as input. - If you are using a custom http handler, you may call
destroy()to close open connections.
// a client can be shared by different commands.
const client = new DataPipelineClient({ region: "REGION" });
const params = {
/** input parameters */
};
const command = new ListPipelinesCommand(params);We recommend using await operator to wait for the promise returned by send operation as follows:
// async/await.
try {
const data = await client.send(command);
// process data.
} catch (error) {
// error handling.
} finally {
// finally.
}Async-await is clean, concise, intuitive, easy to debug and has better error handling as compared to using Promise chains or callbacks.
You can also use Promise chaining to execute send operation.
client.send(command).then(
(data) => {
// process data.
},
(error) => {
// error handling.
}
);Promises can also be called using .catch() and .finally() as follows:
client
.send(command)
.then((data) => {
// process data.
})
.catch((error) => {
// error handling.
})
.finally(() => {
// finally.
});We do not recommend using callbacks because of callback hell, but they are supported by the send operation.
// callbacks.
client.send(command, (err, data) => {
// process err and data.
});The client can also send requests using v2 compatible style. However, it results in a bigger bundle size and may be dropped in next major version. More details in the blog post on modular packages in AWS SDK for JavaScript
import * as AWS from "@aws-sdk/client-data-pipeline";
const client = new AWS.DataPipeline({ region: "REGION" });
// async/await.
try {
const data = await client.listPipelines(params);
// process data.
} catch (error) {
// error handling.
}
// Promises.
client
.listPipelines(params)
.then((data) => {
// process data.
})
.catch((error) => {
// error handling.
});
// callbacks.
client.listPipelines(params, (err, data) => {
// process err and data.
});When the service returns an exception, the error will include the exception information, as well as response metadata (e.g. request id).
try {
const data = await client.send(command);
// process data.
} catch (error) {
const { requestId, cfId, extendedRequestId } = error.$metadata;
console.log({ requestId, cfId, extendedRequestId });
/**
* The keys within exceptions are also parsed.
* You can access them by specifying exception names:
* if (error.name === 'SomeServiceException') {
* const value = error.specialKeyInException;
* }
*/
}Please use these community resources for getting help. We use the GitHub issues for tracking bugs and feature requests, but have limited bandwidth to address them.
- Visit Developer Guide or API Reference.
- Check out the blog posts tagged with
aws-sdk-json AWS Developer Blog. - Ask a question on StackOverflow and tag it with
aws-sdk-js. - Join the AWS JavaScript community on gitter.
- If it turns out that you may have found a bug, please open an issue.
To test your universal JavaScript code in Node.js, browser and react-native environments, visit our code samples repo.
This client code is generated automatically. Any modifications will be overwritten the next time the @aws-sdk/client-data-pipeline package is updated.
To contribute to client you can check our generate clients scripts.
This SDK is distributed under the Apache License, Version 2.0, see LICENSE for more information.