AWS.DynamoDB

Amazon DynamoDB

Overview

This is the Amazon DynamoDB API Reference. This guide provides descriptions and samples of the low-level DynamoDB API. For information about DynamoDB application development, see the Amazon DynamoDB Developer Guide.

Instead of making the requests to the low-level DynamoDB API directly from your application, we recommend that you use the AWS Software Development Kits (SDKs). The easy-to-use libraries in the AWS SDKs make it unnecessary to call the low-level DynamoDB API directly from your application. The libraries take care of request authentication, serialization, and connection management. For more information, see Using the AWS SDKs with DynamoDB in the Amazon DynamoDB Developer Guide.

If you decide to code against the low-level DynamoDB API directly, you will need to write the necessary code to authenticate your requests. For more information on signing your requests, see Using the DynamoDB API in the Amazon DynamoDB Developer Guide.

The following are short descriptions of each low-level API action, organized by function.

Managing Tables

For conceptual information about managing tables, see Working with Tables in the Amazon DynamoDB Developer Guide.

Reading Data

For conceptual information about reading data, see Working with Items and Query and Scan Operations in the Amazon DynamoDB Developer Guide.

Modifying Data

For conceptual information about modifying data, see Working with Items and Query and Scan Operations in the Amazon DynamoDB Developer Guide.

Summary

batch_get_item(client, input, options \\ [])

The BatchGetItem operation returns the attributes of one or more items from one or more tables. You identify requested items by primary key

batch_write_item(client, input, options \\ [])

The 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

create_table(client, input, options \\ [])

The CreateTable operation adds a new table to your account. In an AWS account, table names must be unique within each region. That is, you can have two tables with same name if you create the tables in different regions

delete_item(client, input, options \\ [])

Deletes a single item in a table by primary key. You can perform a conditional delete operation that deletes the item if it exists, or if it has an expected attribute value

delete_table(client, input, options \\ [])

The DeleteTable operation deletes a table and all of its items. After a DeleteTable request, the specified table is in the DELETING state until DynamoDB completes the deletion. If the table is in the ACTIVE state, you can delete it. If a table is in CREATING or UPDATING states, then DynamoDB returns a ResourceInUseException. If the specified table does not exist, DynamoDB returns a ResourceNotFoundException. If table is already in the DELETING state, no error is returned

describe_table(client, input, options \\ [])

Returns information about the table, including the current status of the table, when it was created, the primary key schema, and any indexes on the table

get_item(client, input, options \\ [])

The GetItem operation returns a set of attributes for the item with the given primary key. If there is no matching item, GetItem does not return any data

list_tables(client, input, options \\ [])

Returns an array of table names associated with the current account and endpoint. The output from ListTables is paginated, with each page returning a maximum of 100 table names

put_item(client, input, options \\ [])

Creates a new item, or replaces an old item with a new item. If an item that has the same primary key as the new item already exists in the specified table, the new item completely replaces the existing item. You can perform a conditional put operation (add a new item if one with the specified primary key doesn't exist), or replace an existing item if it has certain attribute values

query(client, input, options \\ [])

A Query operation uses the primary key of a table or a secondary index to directly access items from that table or index

scan(client, input, options \\ [])

The Scan operation returns one or more items and item attributes by accessing every item in a table or a secondary index. To have DynamoDB return fewer items, you can provide a ScanFilter operation

update_item(client, input, options \\ [])

Edits an existing item's attributes, or adds a new item to the table if it does not already exist. You can put, delete, or add attribute values. You can also perform a conditional update on an existing item (insert a new attribute name-value pair if it doesn't exist, or replace an existing name-value pair if it has certain expected attribute values). If conditions are specified and the item does not exist, then the operation fails and a new item is not created

update_table(client, input, options \\ [])

Updates the provisioned throughput for the given table, or manages the global secondary indexes on the table

Functions

batch_get_item(client, input, options \\ [])

The 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 will return 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.

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 data set.

If none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then BatchGetItem will return 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 attributes in any particular order. To help parse the response by item, include the primary key values for the items in your request in the AttributesToGet 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 Capacity Units Calculations in the Amazon DynamoDB Developer Guide.

batch_write_item(client, input, options \\ [])

The 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 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.

Note that if none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then BatchWriteItem will return 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 Elastic MapReduce (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, 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, you must update 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, 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.

  • 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.

create_table(client, input, options \\ [])

The CreateTable operation adds a new table to your account. In an AWS account, table names must be unique within each region. That is, you can have two tables with same name if you create the tables in different regions.

CreateTable is an asynchronous operation. Upon receiving a CreateTable request, DynamoDB immediately returns a response with a TableStatus of CREATING. After the table is created, DynamoDB sets the TableStatus to ACTIVE. You can perform read and write operations only on an ACTIVE table.

You can optionally define secondary indexes on the new table, as part of the CreateTable operation. If you want to create multiple tables with secondary indexes on them, you must create the tables sequentially. Only one table with secondary indexes can be in the CREATING state at any given time.

You can use the DescribeTable API to check the table status.

delete_item(client, input, options \\ [])

Deletes a single item in a table by primary key. You can perform a conditional delete operation that deletes the item if it exists, or if it has an expected attribute value.

In addition to deleting an item, you can also return the item's attribute values in the same operation, using the ReturnValues parameter.

Unless you specify conditions, the DeleteItem is an idempotent operation; running it multiple times on the same item or attribute does not result in an error response.

Conditional deletes are useful for deleting items only if specific conditions are met. If those conditions are met, DynamoDB performs the delete. Otherwise, the item is not deleted.

delete_table(client, input, options \\ [])

The DeleteTable operation deletes a table and all of its items. After a DeleteTable request, the specified table is in the DELETING state until DynamoDB completes the deletion. If the table is in the ACTIVE state, you can delete it. If a table is in CREATING or UPDATING states, then DynamoDB returns a ResourceInUseException. If the specified table does not exist, DynamoDB returns a ResourceNotFoundException. If table is already in the DELETING state, no error is returned.

DynamoDB might continue to accept data read and write operations, such as GetItem and PutItem, on a table in the DELETING state until the table deletion is complete.

When you delete a table, any indexes on that table are also deleted.

Use the DescribeTable API to check the status of the table.

describe_table(client, input, options \\ [])

Returns information about the table, including the current status of the table, when it was created, the primary key schema, and any indexes on the table.

If you issue a DescribeTable request immediately after a CreateTable request, DynamoDB might return a ResourceNotFoundException. This is because DescribeTable uses an eventually consistent query, and the metadata for your table might not be available at that moment. Wait for a few seconds, and then try the DescribeTable request again.

get_item(client, input, options \\ [])

The GetItem operation returns a set of attributes for the item with the given primary key. If there is no matching item, GetItem does not return any data.

GetItem provides an eventually consistent read by default. If your application requires a strongly consistent read, set ConsistentRead to true. Although a strongly consistent read might take more time than an eventually consistent read, it always returns the last updated value.

list_tables(client, input, options \\ [])

Returns an array of table names associated with the current account and endpoint. The output from ListTables is paginated, with each page returning a maximum of 100 table names.

put_item(client, input, options \\ [])

Creates a new item, or replaces an old item with a new item. If an item that has the same primary key as the new item already exists in the specified table, the new item completely replaces the existing item. You can perform a conditional put operation (add a new item if one with the specified primary key doesn't exist), or replace an existing item if it has certain attribute values.

In addition to putting an item, you can also return the item's attribute values in the same operation, using the ReturnValues parameter.

When you add an item, the primary key attribute(s) are the only required attributes. Attribute values cannot be null. String and Binary type attributes must have lengths greater than zero. Set type attributes cannot be empty. Requests with empty values will be rejected with a ValidationException exception.

You can request that PutItem return either a copy of the original item (before the update) or a copy of the updated item (after the update). For more information, see the ReturnValues description below.

To prevent a new item from replacing an existing item, use a conditional put operation with ComparisonOperator set to NULL for the primary key attribute, or attributes.

For more information about using this API, see Working with Items in the Amazon DynamoDB Developer Guide.

query(client, input, options \\ [])

A Query operation uses the primary key of a table or a secondary index to directly access items from that table or index.

Use the KeyConditionExpression parameter to provide a specific hash key value. The Query operation will return all of the items from the table or index with that hash key value. You can optionally narrow the scope of the Query by specifying a range key value and a comparison operator in the KeyConditionExpression. You can use the ScanIndexForward parameter to get results in forward or reverse order, by range key or by index key.

Queries that do not return results consume the minimum number of read capacity units for that type of read operation.

If the total number of items meeting the query criteria exceeds the result set size limit of 1 MB, the query stops and results are returned to the user with LastEvaluatedKey to continue the query in a subsequent operation. Unlike a Scan operation, a Query operation never returns both an empty result set and a LastEvaluatedKey. The LastEvaluatedKey is only provided if the results exceed 1 MB, or if you have used Limit.

You can query a table, a local secondary index, or a global secondary index. For a query on a table or on a local secondary index, you can set ConsistentRead to true and obtain a strongly consistent result. Global secondary indexes support eventually consistent reads only, so do not specify ConsistentRead when querying a global secondary index.

scan(client, input, options \\ [])

The Scan operation returns one or more items and item attributes by accessing every item in a table or a secondary index. To have DynamoDB return fewer items, you can provide a ScanFilter operation.

If the total number of scanned items exceeds the maximum data set size limit of 1 MB, the scan stops and results are returned to the user as a LastEvaluatedKey value to continue the scan in a subsequent operation. The results also include the number of items exceeding the limit. A scan can result in no table data meeting the filter criteria.

The result set is eventually consistent.

By default, Scan operations proceed sequentially; however, for faster performance on a large table or secondary index, applications can request a parallel Scan operation by providing the Segment and TotalSegments parameters. For more information, see Parallel Scan in the Amazon DynamoDB Developer Guide.

update_item(client, input, options \\ [])

Edits an existing item's attributes, or adds a new item to the table if it does not already exist. You can put, delete, or add attribute values. You can also perform a conditional update on an existing item (insert a new attribute name-value pair if it doesn't exist, or replace an existing name-value pair if it has certain expected attribute values). If conditions are specified and the item does not exist, then the operation fails and a new item is not created.

You can also return the item's attribute values in the same UpdateItem operation using the ReturnValues parameter.

update_table(client, input, options \\ [])

Updates the provisioned throughput for the given table, or manages the global secondary indexes on the table.

You can increase or decrease the table's provisioned throughput values within the maximums and minimums listed in the Limits section in the Amazon DynamoDB Developer Guide.

In addition, you can use UpdateTable to add, modify or delete global secondary indexes on the table. For more information, see Managing Global Secondary Indexes in the Amazon DynamoDB Developer Guide.

The table must be in the ACTIVE state for UpdateTable to succeed. UpdateTable is an asynchronous operation; while executing the operation, the table is in the UPDATING state. While the table is in the UPDATING state, the table still has the provisioned throughput from before the call. The table's new provisioned throughput settings go into effect when the table returns to the ACTIVE state; at that point, the UpdateTable operation is complete.