# WARNING: DO NOT EDIT, AUTO-GENERATED CODE!
# See https://github.com/aws-beam/aws-codegen for more details.
defmodule AWS.DynamoDB do
@moduledoc """
Amazon DynamoDB
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and
predictable performance with seamless scalability.
DynamoDB lets you offload the administrative burdens of operating and scaling a
distributed database, so that you don't have to worry about hardware
provisioning, setup and configuration, replication, software patching, or
cluster scaling.
With DynamoDB, you can create database tables that can store and retrieve any
amount of data, and serve any level of request traffic. You can scale up or
scale down your tables' throughput capacity without downtime or performance
degradation, and use the Amazon Web Services Management Console to monitor
resource utilization and performance metrics.
DynamoDB automatically spreads the data and traffic for your tables over a
sufficient number of servers to handle your throughput and storage requirements,
while maintaining consistent and fast performance. All of your data is stored on
solid state disks (SSDs) and automatically replicated across multiple
Availability Zones in an Amazon Web Services Region, providing built-in high
availability and data durability.
"""
alias AWS.Client
alias AWS.Request
def metadata do
%AWS.ServiceMetadata{
abbreviation: "DynamoDB",
api_version: "2012-08-10",
content_type: "application/x-amz-json-1.0",
credential_scope: nil,
endpoint_prefix: "dynamodb",
global?: false,
protocol: "json",
service_id: "DynamoDB",
signature_version: "v4",
signing_name: "dynamodb",
target_prefix: "DynamoDB_20120810"
}
end
@doc """
This operation allows you to perform batch reads or writes on data stored in
DynamoDB, using PartiQL.
The entire batch must consist of either read statements or write statements, you
cannot mix both in one batch.
"""
def batch_execute_statement(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "BatchExecuteStatement", input, options)
end
@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` 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](https://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
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](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithTables.html#CapacityUnitCalculations)
in the *Amazon DynamoDB Developer Guide*.
"""
def batch_get_item(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "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`
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](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ErrorHandling.html#Programming.Errors.BatchOperations)
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.
"""
def batch_write_item(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "BatchWriteItem", input, options)
end
@doc """
Creates a backup for an existing table.
Each time you create an on-demand backup, the entire table data is backed up.
There is no limit to the number of on-demand backups that can be taken.
When you create an on-demand backup, a time marker of the request is cataloged,
and the backup is created asynchronously, by applying all changes until the time
of the request to the last full table snapshot. Backup requests are processed
instantaneously and become available for restore within minutes.
You can call `CreateBackup` at a maximum rate of 50 times per second.
All backups in DynamoDB work without consuming any provisioned throughput on the
table.
If you submit a backup request on 2018-12-14 at 14:25:00, the backup is
guaranteed to contain all data committed to the table up to 14:24:00, and data
committed after 14:26:00 will not be. The backup might contain data
modifications made between 14:24:00 and 14:26:00. On-demand backup does not
support causal consistency.
Along with data, the following are also included on the backups:
* Global secondary indexes (GSIs)
* Local secondary indexes (LSIs)
* Streams
* Provisioned read and write capacity
"""
def create_backup(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "CreateBackup", input, options)
end
@doc """
Creates a global table from an existing table.
A global table creates a replication relationship between two or more DynamoDB
tables with the same table name in the provided Regions.
This operation only applies to [Version 2017.11.29](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V1.html)
of global tables.
If you want to add a new replica table to a global table, each of the following
conditions must be true:
* The table must have the same primary key as all of the other
replicas.
* The table must have the same name as all of the other replicas.
* The table must have DynamoDB Streams enabled, with the stream
containing both the new and the old images of the item.
* None of the replica tables in the global table can contain any
data.
If global secondary indexes are specified, then the following conditions must
also be met:
* The global secondary indexes must have the same name.
* The global secondary indexes must have the same hash key and sort
key (if present).
If local secondary indexes are specified, then the following conditions must
also be met:
* The local secondary indexes must have the same name.
* The local secondary indexes must have the same hash key and sort
key (if present).
Write capacity settings should be set consistently across your replica tables
and secondary indexes. DynamoDB strongly recommends enabling auto scaling to
manage the write capacity settings for all of your global tables replicas and
indexes.
If you prefer to manage write capacity settings manually, you should provision
equal replicated write capacity units to your replica tables. You should also
provision equal replicated write capacity units to matching secondary indexes
across your global table.
"""
def create_global_table(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "CreateGlobalTable", input, options)
end
@doc """
The `CreateTable` operation adds a new table to your account.
In an Amazon Web Services 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` action to check the table status.
"""
def create_table(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "CreateTable", input, options)
end
@doc """
Deletes an existing backup of a table.
You can call `DeleteBackup` at a maximum rate of 10 times per second.
"""
def delete_backup(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DeleteBackup", 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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "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` action to check the status of the table.
"""
def delete_table(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DeleteTable", input, options)
end
@doc """
Describes an existing backup of a table.
You can call `DescribeBackup` at a maximum rate of 10 times per second.
"""
def describe_backup(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeBackup", input, options)
end
@doc """
Checks the status of continuous backups and point in time recovery on the
specified table.
Continuous backups are `ENABLED` on all tables at table creation. If point in
time recovery is enabled, `PointInTimeRecoveryStatus` will be set to ENABLED.
After continuous backups and point in time recovery are enabled, you can restore
to any point in time within `EarliestRestorableDateTime` and
`LatestRestorableDateTime`.
`LatestRestorableDateTime` is typically 5 minutes before the current time. You
can restore your table to any point in time during the last 35 days.
You can call `DescribeContinuousBackups` at a maximum rate of 10 times per
second.
"""
def describe_continuous_backups(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeContinuousBackups", input, options)
end
@doc """
Returns information about contributor insights, for a given table or global
secondary index.
"""
def describe_contributor_insights(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeContributorInsights", input, options)
end
@doc """
Returns the regional endpoint information.
"""
def describe_endpoints(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeEndpoints", input, options)
end
@doc """
Describes an existing table export.
"""
def describe_export(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeExport", input, options)
end
@doc """
Returns information about the specified global table.
This operation only applies to [Version 2017.11.29](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V1.html)
of global tables. If you are using global tables [Version 2019.11.21](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V2.html)
you can use
[DescribeTable](https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_DescribeTable.html)
instead.
"""
def describe_global_table(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeGlobalTable", input, options)
end
@doc """
Describes Region-specific settings for a global table.
This operation only applies to [Version 2017.11.29](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V1.html)
of global tables.
"""
def describe_global_table_settings(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeGlobalTableSettings", input, options)
end
@doc """
Returns information about the status of Kinesis streaming.
"""
def describe_kinesis_streaming_destination(%Client{} = client, input, options \\ []) do
Request.request_post(
client,
metadata(),
"DescribeKinesisStreamingDestination",
input,
options
)
end
@doc """
Returns the current provisioned-capacity quotas for your Amazon Web Services
account in a Region, both for the Region as a whole and for any one DynamoDB
table that you create there.
When you establish an Amazon Web Services account, the account has initial
quotas on the maximum read capacity units and write capacity units that you can
provision across all of your DynamoDB tables in a given Region. Also, there are
per-table quotas that apply when you create a table there. For more information,
see [Service, Account, and Table Quotas](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Limits.html)
page in the *Amazon DynamoDB Developer Guide*.
Although you can increase these quotas by filing a case at [Amazon Web Services Support Center](https://console.aws.amazon.com/support/home#/), obtaining the
increase is not instantaneous. The `DescribeLimits` action lets you write code
to compare the capacity you are currently using to those quotas imposed by your
account so that you have enough time to apply for an increase before you hit a
quota.
For example, you could use one of the Amazon Web Services SDKs to do the
following:
1. Call `DescribeLimits` for a particular Region to obtain your
current account quotas on provisioned capacity there.
2. Create a variable to hold the aggregate read capacity units
provisioned for all your tables in that Region, and one to hold the aggregate
write capacity units. Zero them both.
3. Call `ListTables` to obtain a list of all your DynamoDB tables.
4. For each table name listed by `ListTables`, do the following:
* Call `DescribeTable` with the table name.
* Use the data returned by `DescribeTable` to add the
read capacity units and write capacity units provisioned for the table itself to
your variables.
* If the table has one or more global secondary indexes
(GSIs), loop over these GSIs and add their provisioned capacity values to your
variables as well.
5. Report the account quotas for that Region returned by
`DescribeLimits`, along with the total current provisioned capacity levels you
have calculated.
This will let you see whether you are getting close to your account-level
quotas.
The per-table quotas apply only when you are creating a new table. They restrict
the sum of the provisioned capacity of the new table itself and all its global
secondary indexes.
For existing tables and their GSIs, DynamoDB doesn't let you increase
provisioned capacity extremely rapidly, but the only quota that applies is that
the aggregate provisioned capacity over all your tables and GSIs cannot exceed
either of the per-account quotas.
`DescribeLimits` should only be called periodically. You can expect throttling
errors if you call it more than once in a minute.
The `DescribeLimits` Request element has no content.
"""
def describe_limits(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeLimits", 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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeTable", input, options)
end
@doc """
Describes auto scaling settings across replicas of the global table at once.
This operation only applies to [Version 2019.11.21](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V2.html)
of global tables.
"""
def describe_table_replica_auto_scaling(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeTableReplicaAutoScaling", input, options)
end
@doc """
Gives a description of the Time to Live (TTL) status on the specified table.
"""
def describe_time_to_live(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DescribeTimeToLive", input, options)
end
@doc """
Stops replication from the DynamoDB table to the Kinesis data stream.
This is done without deleting either of the resources.
"""
def disable_kinesis_streaming_destination(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "DisableKinesisStreamingDestination", input, options)
end
@doc """
Starts table data replication to the specified Kinesis data stream at a
timestamp chosen during the enable workflow.
If this operation doesn't return results immediately, use
DescribeKinesisStreamingDestination to check if streaming to the Kinesis data
stream is ACTIVE.
"""
def enable_kinesis_streaming_destination(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "EnableKinesisStreamingDestination", input, options)
end
@doc """
This operation allows you to perform reads and singleton writes on data stored
in DynamoDB, using PartiQL.
"""
def execute_statement(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ExecuteStatement", input, options)
end
@doc """
This operation allows you to perform transactional reads or writes on data
stored in DynamoDB, using PartiQL.
The entire transaction must consist of either read statements or write
statements, you cannot mix both in one transaction. The EXISTS function is an
exception and can be used to check the condition of specific attributes of the
item in a similar manner to `ConditionCheck` in the
[TransactWriteItems](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/transaction-apis.html#transaction-apis-txwriteitems)
API.
"""
def execute_transaction(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ExecuteTransaction", input, options)
end
@doc """
Exports table data to an S3 bucket.
The table must have point in time recovery enabled, and you can export data from
any time within the point in time recovery window.
"""
def export_table_to_point_in_time(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ExportTableToPointInTime", 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 and there will
be no `Item` element in the response.
`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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "GetItem", input, options)
end
@doc """
List backups associated with an Amazon Web Services account.
To list backups for a given table, specify `TableName`. `ListBackups` returns a
paginated list of results with at most 1 MB worth of items in a page. You can
also specify a maximum number of entries to be returned in a page.
In the request, start time is inclusive, but end time is exclusive. Note that
these boundaries are for the time at which the original backup was requested.
You can call `ListBackups` a maximum of five times per second.
"""
def list_backups(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListBackups", input, options)
end
@doc """
Returns a list of ContributorInsightsSummary for a table and all its global
secondary indexes.
"""
def list_contributor_insights(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListContributorInsights", input, options)
end
@doc """
Lists completed exports within the past 90 days.
"""
def list_exports(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListExports", input, options)
end
@doc """
Lists all global tables that have a replica in the specified Region.
This operation only applies to [Version 2017.11.29](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V1.html)
of global tables.
"""
def list_global_tables(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListGlobalTables", 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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListTables", input, options)
end
@doc """
List all tags on an Amazon DynamoDB resource.
You can call ListTagsOfResource up to 10 times per second, per account.
For an overview on tagging DynamoDB resources, see [Tagging for DynamoDB](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Tagging.html)
in the *Amazon DynamoDB Developer Guide*.
"""
def list_tags_of_resource(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "ListTagsOfResource", 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. You can return the item's attribute values in the same
operation, using the `ReturnValues` parameter.
This topic provides general information about the `PutItem` API.
For information on how to call the `PutItem` API using the Amazon Web Services
SDK in specific languages, see the following:
[ PutItem in the Command Line Interface](http://docs.aws.amazon.com/goto/aws-cli/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for .NET](http://docs.aws.amazon.com/goto/DotNetSDKV3/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for C++](http://docs.aws.amazon.com/goto/SdkForCpp/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for Go](http://docs.aws.amazon.com/goto/SdkForGoV1/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for Java](http://docs.aws.amazon.com/goto/SdkForJava/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for JavaScript](http://docs.aws.amazon.com/goto/AWSJavaScriptSDK/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for PHP V3](http://docs.aws.amazon.com/goto/SdkForPHPV3/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for Python (Boto)](http://docs.aws.amazon.com/goto/boto3/dynamodb-2012-08-10/PutItem)
[ PutItem in the SDK for Ruby V2](http://docs.aws.amazon.com/goto/SdkForRubyV2/dynamodb-2012-08-10/PutItem)
When you add an item, the primary key attributes are the only required
attributes. Attribute values cannot be null.
Empty String and Binary attribute values are allowed. Attribute values of type
String and Binary must have a length greater than zero if the attribute is used
as a key attribute for a table or index. Set type attributes cannot be empty.
Invalid Requests with empty values will be rejected with a `ValidationException`
exception.
To prevent a new item from replacing an existing item, use a conditional
expression that contains the `attribute_not_exists` function with the name of
the attribute being used as the partition key for the table. Since every record
must contain that attribute, the `attribute_not_exists` function will only
succeed if no matching item exists.
For more information about `PutItem`, see [Working with Items](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/WorkingWithItems.html)
in the *Amazon DynamoDB Developer Guide*.
"""
def put_item(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "PutItem", input, options)
end
@doc """
You must provide the name of the partition key attribute and a single value for
that attribute.
`Query` returns all items with that partition key value. Optionally, you can
provide a sort key attribute and use a comparison operator to refine the search
results.
Use the `KeyConditionExpression` parameter to provide a specific value for the
partition key. The `Query` operation will return all of the items from the table
or index with that partition key value. You can optionally narrow the scope of
the `Query` operation by specifying a sort key value and a comparison operator
in `KeyConditionExpression`. To further refine the `Query` results, you can
optionally provide a `FilterExpression`. A `FilterExpression` determines which
items within the results should be returned to you. All of the other results are
discarded.
A `Query` operation always returns a result set. If no matching items are found,
the result set will be empty. Queries that do not return results consume the
minimum number of read capacity units for that type of read operation.
DynamoDB calculates the number of read capacity units consumed based on item
size, not on the amount of data that is returned to an application. The number
of capacity units consumed will be the same whether you request all of the
attributes (the default behavior) or just some of them (using a projection
expression). The number will also be the same whether or not you use a
`FilterExpression`.
`Query` results are always sorted by the sort key value. If the data type of the
sort key is Number, the results are returned in numeric order; otherwise, the
results are returned in order of UTF-8 bytes. By default, the sort order is
ascending. To reverse the order, set the `ScanIndexForward` parameter to false.
A single `Query` operation will read up to the maximum number of items set (if
using the `Limit` parameter) or a maximum of 1 MB of data and then apply any
filtering to the results using `FilterExpression`. If `LastEvaluatedKey` is
present in the response, you will need to paginate the result set. For more
information, see [Paginating the Results](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Query.html#Query.Pagination)
in the *Amazon DynamoDB Developer Guide*.
`FilterExpression` is applied after a `Query` finishes, but before the results
are returned. A `FilterExpression` cannot contain partition key or sort key
attributes. You need to specify those attributes in the
`KeyConditionExpression`.
A `Query` operation can return an empty result set and a `LastEvaluatedKey` if
all the items read for the page of results are filtered out.
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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "Query", input, options)
end
@doc """
Creates a new table from an existing backup.
Any number of users can execute up to 4 concurrent restores (any type of
restore) in a given account.
You can call `RestoreTableFromBackup` at a maximum rate of 10 times per second.
You must manually set up the following on the restored table:
* Auto scaling policies
* IAM policies
* Amazon CloudWatch metrics and alarms
* Tags
* Stream settings
* Time to Live (TTL) settings
"""
def restore_table_from_backup(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "RestoreTableFromBackup", input, options)
end
@doc """
Restores the specified table to the specified point in time within
`EarliestRestorableDateTime` and `LatestRestorableDateTime`.
You can restore your table to any point in time during the last 35 days. Any
number of users can execute up to 4 concurrent restores (any type of restore) in
a given account.
When you restore using point in time recovery, DynamoDB restores your table data
to the state based on the selected date and time (day:hour:minute:second) to a
new table.
Along with data, the following are also included on the new restored table using
point in time recovery:
* Global secondary indexes (GSIs)
* Local secondary indexes (LSIs)
* Provisioned read and write capacity
* Encryption settings
All these settings come from the current settings of the source table at the
time of restore.
You must manually set up the following on the restored table:
* Auto scaling policies
* IAM policies
* Amazon CloudWatch metrics and alarms
* Tags
* Stream settings
* Time to Live (TTL) settings
* Point in time recovery settings
"""
def restore_table_to_point_in_time(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "RestoreTableToPointInTime", 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 `FilterExpression`
operation.
If the total number of scanned items exceeds the maximum dataset 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.
A single `Scan` operation reads up to the maximum number of items set (if using
the `Limit` parameter) or a maximum of 1 MB of data and then apply any filtering
to the results using `FilterExpression`. If `LastEvaluatedKey` is present in the
response, you need to paginate the result set. For more information, see
[Paginating the Results](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.Pagination)
in the *Amazon DynamoDB Developer Guide*.
`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](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.ParallelScan)
in the *Amazon DynamoDB Developer Guide*.
`Scan` uses eventually consistent reads when accessing the data in a table;
therefore, the result set might not include the changes to data in the table
immediately before the operation began. If you need a consistent copy of the
data, as of the time that the `Scan` begins, you can set the `ConsistentRead`
parameter to `true`.
"""
def scan(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "Scan", input, options)
end
@doc """
Associate a set of tags with an Amazon DynamoDB resource.
You can then activate these user-defined tags so that they appear on the Billing
and Cost Management console for cost allocation tracking. You can call
TagResource up to five times per second, per account.
For an overview on tagging DynamoDB resources, see [Tagging for DynamoDB](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Tagging.html)
in the *Amazon DynamoDB Developer Guide*.
"""
def tag_resource(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "TagResource", input, options)
end
@doc """
`TransactGetItems` is a synchronous operation that atomically retrieves multiple
items from one or more tables (but not from indexes) in a single account and
Region.
A `TransactGetItems` call can contain up to 25 `TransactGetItem` objects, each
of which contains a `Get` structure that specifies an item to retrieve from a
table in the account and Region. A call to `TransactGetItems` cannot retrieve
items from tables in more than one Amazon Web Services account or Region. The
aggregate size of the items in the transaction cannot exceed 4 MB.
DynamoDB rejects the entire `TransactGetItems` request if any of the following
is true:
* A conflicting operation is in the process of updating an item to
be read.
* There is insufficient provisioned capacity for the transaction to
be completed.
* There is a user error, such as an invalid data format.
* The aggregate size of the items in the transaction cannot exceed 4
MB.
"""
def transact_get_items(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "TransactGetItems", input, options)
end
@doc """
`TransactWriteItems` is a synchronous write operation that groups up to 25
action requests.
These actions can target items in different tables, but not in different Amazon
Web Services accounts or Regions, and no two actions can target the same item.
For example, you cannot both `ConditionCheck` and `Update` the same item. The
aggregate size of the items in the transaction cannot exceed 4 MB.
The actions are completed atomically so that either all of them succeed, or all
of them fail. They are defined by the following objects:
* `Put` — Initiates a `PutItem` operation to write a new item.
This structure specifies the primary key of the item to be written, the name of
the table to write it in, an optional condition expression that must be
satisfied for the write to succeed, a list of the item's attributes, and a field
indicating whether to retrieve the item's attributes if the condition is not
met.
* `Update` — Initiates an `UpdateItem` operation to update an
existing item. This structure specifies the primary key of the item to be
updated, the name of the table where it resides, an optional condition
expression that must be satisfied for the update to succeed, an expression that
defines one or more attributes to be updated, and a field indicating whether to
retrieve the item's attributes if the condition is not met.
* `Delete` — Initiates a `DeleteItem` operation to delete an
existing item. This structure specifies the primary key of the item to be
deleted, the name of the table where it resides, an optional condition
expression that must be satisfied for the deletion to succeed, and a field
indicating whether to retrieve the item's attributes if the condition is not
met.
* `ConditionCheck` — Applies a condition to an item that is not
being modified by the transaction. This structure specifies the primary key of
the item to be checked, the name of the table where it resides, a condition
expression that must be satisfied for the transaction to succeed, and a field
indicating whether to retrieve the item's attributes if the condition is not
met.
DynamoDB rejects the entire `TransactWriteItems` request if any of the following
is true:
* A condition in one of the condition expressions is not met.
* An ongoing operation is in the process of updating the same item.
* There is insufficient provisioned capacity for the transaction to
be completed.
* An item size becomes too large (bigger than 400 KB), a local
secondary index (LSI) becomes too large, or a similar validation error occurs
because of changes made by the transaction.
* The aggregate size of the items in the transaction exceeds 4 MB.
* There is a user error, such as an invalid data format.
"""
def transact_write_items(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "TransactWriteItems", input, options)
end
@doc """
Removes the association of tags from an Amazon DynamoDB resource.
You can call `UntagResource` up to five times per second, per account.
For an overview on tagging DynamoDB resources, see [Tagging for DynamoDB](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Tagging.html)
in the *Amazon DynamoDB Developer Guide*.
"""
def untag_resource(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UntagResource", input, options)
end
@doc """
`UpdateContinuousBackups` enables or disables point in time recovery for the
specified table.
A successful `UpdateContinuousBackups` call returns the current
`ContinuousBackupsDescription`. Continuous backups are `ENABLED` on all tables
at table creation. If point in time recovery is enabled,
`PointInTimeRecoveryStatus` will be set to ENABLED.
Once continuous backups and point in time recovery are enabled, you can restore
to any point in time within `EarliestRestorableDateTime` and
`LatestRestorableDateTime`.
`LatestRestorableDateTime` is typically 5 minutes before the current time. You
can restore your table to any point in time during the last 35 days.
"""
def update_continuous_backups(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateContinuousBackups", input, options)
end
@doc """
Updates the status for contributor insights for a specific table or index.
CloudWatch Contributor Insights for DynamoDB graphs display the partition key
and (if applicable) sort key of frequently accessed items and frequently
throttled items in plaintext. If you require the use of AWS Key Management
Service (KMS) to encrypt this table’s partition key and sort key data with an
AWS managed key or customer managed key, you should not enable CloudWatch
Contributor Insights for DynamoDB for this table.
"""
def update_contributor_insights(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateContributorInsights", input, options)
end
@doc """
Adds or removes replicas in the specified global table.
The global table must already exist to be able to use this operation. Any
replica to be added must be empty, have the same name as the global table, have
the same key schema, have DynamoDB Streams enabled, and have the same
provisioned and maximum write capacity units.
Although you can use `UpdateGlobalTable` to add replicas and remove replicas in
a single request, for simplicity we recommend that you issue separate requests
for adding or removing replicas.
If global secondary indexes are specified, then the following conditions must
also be met:
* The global secondary indexes must have the same name.
* The global secondary indexes must have the same hash key and sort
key (if present).
* The global secondary indexes must have the same provisioned and
maximum write capacity units.
"""
def update_global_table(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateGlobalTable", input, options)
end
@doc """
Updates settings for a global table.
"""
def update_global_table_settings(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateGlobalTableSettings", 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).
You can also return the item's attribute values in the same `UpdateItem`
operation using the `ReturnValues` parameter.
"""
def update_item(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "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:
* Modify the provisioned throughput settings of the table.
* Enable or disable DynamoDB Streams on the table.
* Remove a global secondary index from the table.
* Create a new global secondary index on the table. After the index
begins backfilling, you can use `UpdateTable` to perform other operations.
`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{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateTable", input, options)
end
@doc """
Updates auto scaling settings on your global tables at once.
This operation only applies to [Version 2019.11.21](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables.V2.html)
of global tables.
"""
def update_table_replica_auto_scaling(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateTableReplicaAutoScaling", input, options)
end
@doc """
The `UpdateTimeToLive` method enables or disables Time to Live (TTL) for the
specified table.
A successful `UpdateTimeToLive` call returns the current
`TimeToLiveSpecification`. It can take up to one hour for the change to fully
process. Any additional `UpdateTimeToLive` calls for the same table during this
one hour duration result in a `ValidationException`.
TTL compares the current time in epoch time format to the time stored in the TTL
attribute of an item. If the epoch time value stored in the attribute is less
than the current time, the item is marked as expired and subsequently deleted.
The epoch time format is the number of seconds elapsed since 12:00:00 AM January
1, 1970 UTC.
DynamoDB deletes expired items on a best-effort basis to ensure availability of
throughput for other data operations.
DynamoDB typically deletes expired items within two days of expiration. The
exact duration within which an item gets deleted after expiration is specific to
the nature of the workload. Items that have expired and not been deleted will
still show up in reads, queries, and scans.
As items are deleted, they are removed from any local secondary index and global
secondary index immediately in the same eventually consistent way as a standard
delete operation.
For more information, see [Time To Live](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html)
in the Amazon DynamoDB Developer Guide.
"""
def update_time_to_live(%Client{} = client, input, options \\ []) do
Request.request_post(client, metadata(), "UpdateTimeToLive", input, options)
end
end
