# WARNING: DO NOT EDIT, AUTO-GENERATED CODE! # See https://github.com/jkakar/aws-codegen for more details. defmodule AWS.DynamoDB do @moduledoc """ 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/). 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/UsingAWSSDK.html) 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/API.html) 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithTables.html) in the *Amazon DynamoDB Developer Guide*. **Reading Data** For conceptual information about reading data, see [Working with Items](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html) and [Query and Scan Operations](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/QueryAndScan.html) in the *Amazon DynamoDB Developer Guide*. **Modifying Data** For conceptual information about modifying data, see [Working with Items](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html) and [Query and Scan Operations](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/QueryAndScan.html) in the *Amazon DynamoDB Developer Guide*. """ @doc """ 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. If you request more than 100 items *BatchGetItem* will return 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 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ErrorHandling.html#BatchOperations) 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithTables.html#CapacityUnitCalculations) in the *Amazon DynamoDB Developer Guide*. """ def batch_get_item(client, input, options \\ []) do request(client, "BatchGetItem", input, options) end @doc """ 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ErrorHandling.html#BatchOperations) 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, 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* 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: """ def batch_write_item(client, input, options \\ []) do request(client, "BatchWriteItem", input, options) end @doc """ 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. """ def create_table(client, input, options \\ []) do request(client, "CreateTable", input, options) end @doc """ 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. """ def delete_item(client, input, options \\ []) do request(client, "DeleteItem", input, options) end @doc """ 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. If you have DynamoDB Streams enabled on the table, then the corresponding stream on that table goes into the `DISABLED` state, and the stream is automatically deleted after 24 hours. Use the *DescribeTable* API to check the status of the table. """ def delete_table(client, input, options \\ []) do request(client, "DeleteTable", input, options) end @doc """ 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. """ def describe_table(client, input, options \\ []) do request(client, "DescribeTable", input, options) end @doc """ 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. """ def get_item(client, input, options \\ []) do request(client, "GetItem", input, options) end @doc """ 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. """ def list_tables(client, input, options \\ []) do request(client, "ListTables", input, options) end @doc """ 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html) in the *Amazon DynamoDB Developer Guide*. """ def put_item(client, input, options \\ []) do request(client, "PutItem", input, options) end @doc """ 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* operation by specifying a range key value and a comparison operator in *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 the *LastEvaluatedKey* element 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* value. *LastEvaluatedKey* is only provided if the results exceed 1 MB, or if you have used the *Limit* parameter. 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 the *ConsistentRead* parameter 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. """ def query(client, input, options \\ []) do request(client, "Query", input, options) end @doc """ 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. 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](http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/QueryAndScan.html#QueryAndScanParallelScan) in the *Amazon DynamoDB Developer Guide*. By default, *Scan* uses eventually consistent reads when acessing the data in the table or local secondary index. However, you can use strongly consistent reads instead by setting the *ConsistentRead* parameter to *true*. """ def scan(client, input, options \\ []) do request(client, "Scan", input, options) end @doc """ 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. """ def update_item(client, input, options \\ []) do request(client, "UpdateItem", input, options) end @doc """ Modifies the provisioned throughput settings, global secondary indexes, or DynamoDB Streams settings for a given table. You can only perform one of the following operations at once: *UpdateTable* is an asynchronous operation; while it is executing, the table status changes from `ACTIVE` to `UPDATING`. While it is `UPDATING`, you cannot issue another *UpdateTable* request. When the table returns to the `ACTIVE` state, the *UpdateTable* operation is complete. """ def update_table(client, input, options \\ []) do request(client, "UpdateTable", input, options) end defp request(client, action, input, options) do client = %{client | service: "dynamodb"} host = "dynamodb.#{client.region}.#{client.endpoint}" url = "https://#{host}/" headers = [{"Host", host}, {"Content-Type", "application/x-amz-json-1.0"}, {"X-Amz-Target", "DynamoDB_20120810.#{action}"}] payload = Poison.Encoder.encode(input, []) headers = AWS.Request.sign_v4(client, "POST", url, headers, payload) case HTTPoison.post(url, payload, headers, options) do {:ok, response=%HTTPoison.Response{status_code: 200, body: ""}} -> {:ok, response} {:ok, response=%HTTPoison.Response{status_code: 200, body: body}} -> {:ok, Poison.Parser.parse!(body), response} {:ok, _response=%HTTPoison.Response{body: body}} -> reason = Poison.Parser.parse!(body)["__type"] {:error, reason} {:error, %HTTPoison.Error{reason: reason}} -> {:error, %HTTPoison.Error{reason: reason}} end end end