The BatchWriteItem operation puts or deletes multiple items in one or more tables. A single call to BatchWriteItem can write up to 1 MB of data, which can comprise as many as 25 put or delete requests. Individual items to be written can be as large as 64 KB.
NOTE: BatchWriteItem cannot update items. To update items, use the UpdateItem API.
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.
To write one item, you can use the PutItem operation; to delete one item, you can use the DeleteItem operation.
With BatchWriteItem , you can efficiently write or delete large amounts of data, such as from Amazon Elastic MapReduce (EMR), or copy data from another database into Amazon 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, such as Java, 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, such as PHP, BatchWriteItem will write or delete the specified items one at a time. In both situations, BatchWriteItem provides an alternative where the API 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, Amazon 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.
The total request size exceeds 1 MB.
Any individual item in a batch exceeds 64 KB.
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