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Amazon aws dynamodb client
Amazon aws dynamodb client











In the corresponding table's primary key schema. Primary key attributes specified on an item in the request do not match those

amazon aws dynamodb client

One or more tables specified in the BatchWriteItem request does If one or more of the following is true, DynamoDB rejects the entire batch write Delete operations on nonexistent items consume one write capacity unit. Parallel processing reduces latency, but each specified put and delete requestĬonsumes the same number of write capacity units whether it is processed in parallel or Pool approach without having to introduce complexity into your application. The specified put and delete operations in parallel, giving you the power of the thread In both situations, BatchWriteItem performs

AMAZON AWS DYNAMODB CLIENT UPDATE

With languages that don't support threading, you must update or delete the Your application must include the necessary logic to manage the If you use a programming language that supports concurrency, you can use threads to For example, youĬannot specify conditions on individual put and delete requests, andīatchWriteItem does not return deleted items in the response. Order to improve performance with these large-scale operations,īatchWriteItem does not behave in the same way as individual With BatchWriteItem, you can efficiently write or delete large amounts ofĭata, such as from Amazon EMR, or copy data from another database into DynamoDB. Requests in the batch are much more likely to succeed.įor more information, see Batch Operations and Error Handling in the Amazon DynamoDB If you delay the batch operation using exponential backoff, the individual Underlying read or write requests can still fail due to throttling on the individual If you retry the batch operation immediately, the However, we strongly recommend that you use an exponentialīackoff algorithm. If DynamoDB returns any unprocessed items, you should retry the batch operation on Provisioned throughput on all of the tables in the request, then If none of the items can be processed due to insufficient Items and submit a new BatchWriteItem request with those unprocessed items Each iteration would check for unprocessed Typically, you would callīatchWriteItem in a loop. Investigate and optionally resend the requests. Throughput is exceeded or an internal processing failure occurs, the failed operationsĪre returned in the UnprocessedItems response parameter. If any requested operations fail because the table's provisioned In BatchWriteItem are atomic however BatchWriteItem as a The individual PutItem and DeleteItem operations specified

amazon aws dynamodb client

For more details on this distinction, see Naming Rules and Data Types.īatchWriteItem cannot update items.

amazon aws dynamodb client

Note that an item's representation might be greater than 400KB while being sent inĭynamoDB's JSON format for the API call. Individual items can be up to 400 KB once stored, it's important to A single call to BatchWriteItem can transmit up to 16MB ofĭata over the network, consisting of up to 25 item put or delete operations. The BatchWriteItem operation puts or deletes multiple items in one or











Amazon aws dynamodb client