Download a file in chunks concurrently

Use Transfer Manager to download a single large file in chunks, with concurrency.

Explore further

For detailed documentation that includes this code sample, see the following:

• Sliced object downloads

Code sample

Java

For more information, see the Cloud Storage Java API reference documentation.

To authenticate to Cloud Storage, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

import com.google.cloud.storage.BlobInfo;
import com.google.cloud.storage.transfermanager.DownloadResult;
import com.google.cloud.storage.transfermanager.ParallelDownloadConfig;
import com.google.cloud.storage.transfermanager.TransferManager;
import com.google.cloud.storage.transfermanager.TransferManagerConfig;
import java.nio.file.Path;
import java.util.List;

class AllowDivideAndConquerDownload {

  public static void divideAndConquerDownloadAllowed(
      List<BlobInfo> blobs, String bucketName, Path destinationDirectory) {
    TransferManager transferManager =
        TransferManagerConfig.newBuilder()
            .setAllowDivideAndConquerDownload(true)
            .build()
            .getService();
    ParallelDownloadConfig parallelDownloadConfig =
        ParallelDownloadConfig.newBuilder()
            .setBucketName(bucketName)
            .setDownloadDirectory(destinationDirectory)
            .build();
    List<DownloadResult> results =
        transferManager.downloadBlobs(blobs, parallelDownloadConfig).getDownloadResults();

    for (DownloadResult result : results) {
      System.out.println(
          "Download of "
              + result.getInput().getName()
              + " completed with status "
              + result.getStatus());
    }
  }
}

Node.js

For more information, see the Cloud Storage Node.js API reference documentation.

To authenticate to Cloud Storage, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// The ID of your GCS bucket
// const bucketName = 'your-unique-bucket-name';

// The ID of the GCS file to download
// const fileName = 'your-file-name';

// The path to which the file should be downloaded
// const destFileName = '/local/path/to/file.txt';

// The size of each chunk to be downloaded
// const chunkSize = 1024;

// Imports the Google Cloud client library
const {Storage, TransferManager} = require('@google-cloud/storage');

// Creates a client
const storage = new Storage();

// Creates a transfer manager client
const transferManager = new TransferManager(storage.bucket(bucketName));

async function downloadFileInChunksWithTransferManager() {
  // Downloads the files
  await transferManager.downloadFileInChunks(fileName, {
    destination: destFileName,
    chunkSizeBytes: chunkSize,
  });

  console.log(
    `gs://${bucketName}/${fileName} downloaded to ${destFileName}.`
  );
}

downloadFileInChunksWithTransferManager().catch(console.error);

Python

For more information, see the Cloud Storage Python API reference documentation.

To authenticate to Cloud Storage, set up Application Default Credentials. For more information, see Set up authentication for client libraries.

def download_chunks_concurrently(
    bucket_name, blob_name, filename, chunk_size=32 * 1024 * 1024, workers=8
):
    """Download a single file in chunks, concurrently in a process pool."""

    # The ID of your GCS bucket
    # bucket_name = "your-bucket-name"

    # The file to be downloaded
    # blob_name = "target-file"

    # The destination filename or path
    # filename = ""

    # The size of each chunk. The performance impact of this value depends on
    # the use case. The remote service has a minimum of 5 MiB and a maximum of
    # 5 GiB.
    # chunk_size = 32 * 1024 * 1024 (32 MiB)

    # The maximum number of processes to use for the operation. The performance
    # impact of this value depends on the use case, but smaller files usually
    # benefit from a higher number of processes. Each additional process occupies
    # some CPU and memory resources until finished. Threads can be used instead
    # of processes by passing `worker_type=transfer_manager.THREAD`.
    # workers=8

    from google.cloud.storage import Client, transfer_manager

    storage_client = Client()
    bucket = storage_client.bucket(bucket_name)
    blob = bucket.blob(blob_name)

    transfer_manager.download_chunks_concurrently(
        blob, filename, chunk_size=chunk_size, max_workers=workers
    )

    print("Downloaded {} to {}.".format(blob_name, filename))

What's next

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