Carregamentos multipartes da API XML

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

// The path of file to upload
// const filePath = 'path/to/your/file';

// The size of each chunk to be uploaded
// const chunkSize = 32 * 1024 * 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 uploadFileInChunksWithTransferManager() {
  // Uploads the files
  await transferManager.uploadFileInChunks(filePath, {
    chunkSizeBytes: chunkSize,
  });

  console.log(`${filePath} uploaded to ${bucketName}.`);
}

uploadFileInChunksWithTransferManager().catch(console.error);

def upload_chunks_concurrently(
    bucket_name,
    source_filename,
    destination_blob_name,
    chunk_size=32 * 1024 * 1024,
    workers=8,
):
    """Upload a single file, in chunks, concurrently in a process pool."""
    # The ID of your GCS bucket
    # bucket_name = "your-bucket-name"

    # The path to your file to upload
    # source_filename = "local/path/to/file"

    # The ID of your GCS object
    # destination_blob_name = "storage-object-name"

    # 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. 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(destination_blob_name)

    transfer_manager.upload_chunks_concurrently(
        source_filename, blob, chunk_size=chunk_size, max_workers=workers
    )

    print(f"File {source_filename} uploaded to {destination_blob_name}.")


if __name__ == "__main__":
    argparse = argparse.ArgumentParser(
        description="Upload a file to GCS in chunks concurrently."
    )
    argparse.add_argument(
        "--bucket_name", help="The name of the GCS bucket to upload to."
    )
    argparse.add_argument(
        "--source_filename", help="The local path to the file to upload."
    )
    argparse.add_argument(
        "--destination_blob_name", help="The name of the object in GCS."
    )
    argparse.add_argument(
        "--chunk_size",
        type=int,
        default=32 * 1024 * 1024,
        help="The size of each chunk in bytes (default: 32 MiB). The remote\
              service has a minimum of 5 MiB and a maximum of 5 GiB",
    )
    argparse.add_argument(
        "--workers",
        type=int,
        default=8,
        help="The number of worker processes to use (default: 8).",
    )
    args = argparse.parse_args()
    upload_chunks_concurrently(
        args.bucket_name,
        args.source_filename,
        args.destination_blob_name,
        args.chunk_size,
        args.workers,
    )