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.
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, 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.