You are viewing documentation for version 2 of the AWS SDK for Ruby. Version 3 documentation can be found here.
Class: Aws::DynamoDB::Resource OverviewThis class provides a resource oriented interface for DynamoDB. To create a resource object:
resource = Aws::DynamoDB::Resource.new
You can supply a client object with custom configuration that will be used for all resource operations. If you do not pass :client, a default client will be constructed.
client = Aws::DynamoDB::Client.new(region: 'us-west-2')
resource = Aws::DynamoDB::Resource.new(client: client)
Aws::DynamoDB::Resource has the following resource classes:
Attribute Summary collapseThe BatchGetItem operation returns the attributes of one or more items from one or more tables.
The BatchWriteItem operation puts or deletes multiple items in one or more tables.
Returns a Collection of Table resources.
add_data_attribute, add_identifier, #data, data_attributes, #data_loaded?, identifiers, #load, #wait_until
Methods included from Resources::OperationMethods#add_batch_operation, #add_operation, #batch_operation, #batch_operation_names, #batch_operations, #operation, #operation_names, #operations
Constructor Details #initialize(options = {}) ⇒ Object #initialize(options = {}) ⇒ Object Instance Method Details #batch_get_item(options = {}) ⇒ Types::BatchGetItemOutputThe BatchGetItem operation returns the attributes of one or more items from one or more tables. You identify requested items by primary key.
A single operation can retrieve up to 16 MB of data, which can contain as many as 100 items. BatchGetItem returns a partial result if the response size limit is exceeded, the table's provisioned throughput is exceeded, or an internal processing failure occurs. If a partial result is returned, the operation returns a value for UnprocessedKeys. You can use this value to retry the operation starting with the next item to get.
If you request more than 100 items, BatchGetItem returns a ValidationException with the message "Too many items requested for the BatchGetItem call."
For example, if you ask to retrieve 100 items, but each individual item is 300 KB in size, the system returns 52 items (so as not to exceed the 16 MB limit). It also returns an appropriate UnprocessedKeys value so you can get the next page of results. If desired, your application can include its own logic to assemble the pages of results into one dataset.
If none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then BatchGetItem returns a ProvisionedThroughputExceededException. If at least one of the items is successfully processed, then BatchGetItem completes successfully, while returning the keys of the unread items in UnprocessedKeys.
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.
By default, BatchGetItem performs eventually consistent reads on every table in the request. If you want strongly consistent reads instead, you can set ConsistentRead to true for any or all tables.
In order to minimize response latency, BatchGetItem retrieves items in parallel.
When designing your application, keep in mind that DynamoDB does not return items in any particular order. To help parse the response by item, include the primary key values for the items in your request in the ProjectionExpression parameter.
If a requested item does not exist, it is not returned in the result. Requests for nonexistent items consume the minimum read capacity units according to the type of read. For more information, see Working with Tables in the Amazon DynamoDB Developer Guide.
#batch_write_item(options = {}) ⇒ Types::BatchWriteItemOutputThe BatchWriteItem operation puts or deletes multiple items in one or more tables. A single call to BatchWriteItem can write up to 16 MB of data, which can comprise as many as 25 put or delete requests. Individual items to be written can be as large as 400 KB.
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.
Returns a Collection of Table resources. No API requests are made until you call an enumerable method on the collection. Client#list_tables will be called multiple times until every Table has been yielded.
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