'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, go to `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.
:type request_items: map
:param request_items:
A map of one or more table names and, for each table, a list of
operations to be performed ( DeleteRequest or PutRequest ). Each
element in the map consists of the following:
+ DeleteRequest - Perform a DeleteItem operation on the specified item.
The item to be deleted is identified by a Key subelement:
+ Key - A map of primary key attribute values that uniquely identify
the ! item. Each entry in this map consists of an attribute name
and an attribute value. For each primary key, you must provide all
of the key attributes. For example, with a hash type primary key,
you only need to specify the hash attribute. For a hash-and-range
type primary key, you must specify both the hash attribute and the
range attribute.
+ PutRequest - Perform a PutItem operation on the specified item. The
item to be put is identified by an Item subelement:
+ Item - A map of attributes and their values. Each entry in this map
consists of an attribute name and an attribute value. Attribute
values must not be null; string and binary type attributes must
have lengths greater than zero; and set type attributes must not be
empty. Requests that contain empty values will be rejected with a
ValidationException exception. If you specify any attributes that
are part of an index key, then the data types for those attributes
must match those of the schema in the table\'s attribute definition.
:type return_consumed_capacity: string
:param return_consumed_capacity: A value that if set to `TOTAL`, the
response includes ConsumedCapacity data for tables and indexes. If
set to `INDEXES`, the response includes ConsumedCapacity for
indexes. If set to `NONE` (the default), ConsumedCapacity is not
included in the response.
:type return_item_collection_metrics: string
:param return_item_collection_metrics: A value that if set to `SIZE`,
the response includes statistics about item collections, if any,
that were modified during the operation are returned in the
response. If set to `NONE` (the default), no statistics are
returned.'

def batch_write_item(self, request_items, return_consumed_capacity=None, return_item_collection_metrics=None):

    params = {'RequestItems': request_items}
    if (return_consumed_capacity is not None):
        params['ReturnConsumedCapacity'] = return_consumed_capacity
    if (return_item_collection_metrics is not None):
        params['ReturnItemCollectionMetrics'] = return_item_collection_metrics
    return self.make_request(action='BatchWriteItem', body=json.dumps(params))
