The BatchWriteItem operation puts or deletes multiple items in one or
more tables. A single call to BatchWriteItem can transmit up to 16MB of
data over the network, consisting of up to 25 item put or delete operations. While
individual items can be up to 400 KB once stored, it's important to
note that an item's representation might be greater than 400KB while being sent in
DynamoDB's JSON format for the API call. For more details on this distinction, see Naming Rules and Data Types.
BatchWriteItem cannot update items. To update items, use the
UpdateItem action.
The individual PutItem and DeleteItem operations specified
in BatchWriteItem are atomic; however BatchWriteItem as a
whole is not. If any requested operations fail because the table's provisioned
throughput is exceeded or an internal processing failure occurs, the failed operations
are returned in the UnprocessedItems response parameter. You can
investigate and optionally resend the requests. Typically, you would call
BatchWriteItem in a loop. Each iteration would check for unprocessed
items and submit a new BatchWriteItem request with those unprocessed items
until all items have been processed.
If none of the items can be processed due to insufficient
provisioned throughput on all of the tables in the request, then
BatchWriteItem returns a
ProvisionedThroughputExceededException.
If DynamoDB returns any unprocessed items, you should retry the batch operation on
those items. However, we strongly recommend that you use an exponential
backoff algorithm. If you retry the batch operation immediately, the
underlying read or write requests can still fail due to throttling on the individual
tables. If you delay the batch operation using exponential backoff, the individual
requests in the batch are much more likely to succeed.
With BatchWriteItem, you can efficiently write or delete large amounts of
data, such as from Amazon EMR, or copy data from another database into DynamoDB. In
order to improve performance with these large-scale operations,
BatchWriteItem does not behave in the same way as individual
PutItem and DeleteItem calls would. For example, you
cannot specify conditions on individual put and delete requests, and
BatchWriteItem does not return deleted items in the response.
If you use a programming language that supports concurrency, you can use threads to
write items in parallel. Your application must include the necessary logic to manage the
threads. With languages that don't support threading, you must update or delete the
specified items one at a time. In both situations, BatchWriteItem performs
the specified put and delete operations in parallel, giving you the power of the thread
pool approach without having to introduce complexity into your application.
Parallel processing reduces latency, but each specified put and delete request
consumes the same number of write capacity units whether it is processed in parallel or
not. Delete operations on nonexistent items consume one write capacity unit.
If one or more of the following is true, DynamoDB rejects the entire batch write
operation:
One or more tables specified in the BatchWriteItem request does
not exist.
Primary key attributes specified on an item in the request do not match those
in the corresponding table's primary key schema.
You try to perform multiple operations on the same item in the same
BatchWriteItem request. For example, you cannot put and delete
the same item in the same BatchWriteItem request.
Your request contains at least two items with identical hash and range keys
(which essentially is two put operations).
There are more than 25 requests in the batch.
Any individual item in a batch exceeds 400 KB.
The total request size exceeds 16 MB.
example
Use a bare-bones client and the command you need to make an API call.
The
BatchWriteItemoperation puts or deletes multiple items in one or more tables. A single call toBatchWriteItemcan transmit up to 16MB of data over the network, consisting of up to 25 item put or delete operations. While individual items can be up to 400 KB once stored, it's important to note that an item's representation might be greater than 400KB while being sent in DynamoDB's JSON format for the API call. For more details on this distinction, see Naming Rules and Data Types.BatchWriteItemcannot update items. To update items, use theUpdateItemaction.The individual
PutItemandDeleteItemoperations specified inBatchWriteItemare atomic; howeverBatchWriteItemas a whole is not. If any requested operations fail because the table's provisioned throughput is exceeded or an internal processing failure occurs, the failed operations are returned in theUnprocessedItemsresponse parameter. You can investigate and optionally resend the requests. Typically, you would callBatchWriteItemin a loop. Each iteration would check for unprocessed items and submit a newBatchWriteItemrequest with those unprocessed items until all items have been processed.If none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then
BatchWriteItemreturns aProvisionedThroughputExceededException.If DynamoDB returns any unprocessed items, you should retry the batch operation on those items. However, we strongly recommend that you use an exponential backoff algorithm. If you retry the batch operation immediately, the underlying read or write requests can still fail due to throttling on the individual tables. If you delay the batch operation using exponential backoff, the individual requests in the batch are much more likely to succeed.
For more information, see Batch Operations and Error Handling in the Amazon DynamoDB Developer Guide.
With
BatchWriteItem, you can efficiently write or delete large amounts of data, such as from Amazon EMR, or copy data from another database into DynamoDB. In order to improve performance with these large-scale operations,BatchWriteItemdoes not behave in the same way as individualPutItemandDeleteItemcalls would. For example, you cannot specify conditions on individual put and delete requests, andBatchWriteItemdoes not return deleted items in the response.If you use a programming language that supports concurrency, you can use threads to write items in parallel. Your application must include the necessary logic to manage the threads. With languages that don't support threading, you must update or delete the specified items one at a time. In both situations,
BatchWriteItemperforms the specified put and delete operations in parallel, giving you the power of the thread pool approach without having to introduce complexity into your application.Parallel processing reduces latency, but each specified put and delete request consumes the same number of write capacity units whether it is processed in parallel or not. Delete operations on nonexistent items consume one write capacity unit.
If one or more of the following is true, DynamoDB rejects the entire batch write operation:
One or more tables specified in the
BatchWriteItemrequest does not exist.Primary key attributes specified on an item in the request do not match those in the corresponding table's primary key schema.
You try to perform multiple operations on the same item in the same
BatchWriteItemrequest. For example, you cannot put and delete the same item in the sameBatchWriteItemrequest.Your request contains at least two items with identical hash and range keys (which essentially is two put operations).
There are more than 25 requests in the batch.
Any individual item in a batch exceeds 400 KB.
The total request size exceeds 16 MB.
Use a bare-bones client and the command you need to make an API call.
import { DynamoDBClient, BatchWriteItemCommand } from "@aws-sdk/client-dynamodb"; // ES Modules import // const { DynamoDBClient, BatchWriteItemCommand } = require("@aws-sdk/client-dynamodb"); // CommonJS import const client = new DynamoDBClient(config); const command = new BatchWriteItemCommand(input); const response = await client.send(command);BatchWriteItemCommandInput for command's
inputshape.BatchWriteItemCommandOutput for command's
responseshape.config for DynamoDBClient's
configshape.