<!-- Love localstack? Please consider supporting our collective:
👉  https://opencollective.com/localstack/donate -->

# Type of request: This is a ...

[ ] bug report
[X ] feature request

# Detailed description

I'm using localstack to create a dynamoDb table locally with a dynamodb stream and a flink application consuming data from the stream
The shardId created in localstack follows this format

shardId-000000000000-798cedd84a2953c5af70a131f8701f35

Flink expects this format
shardId-00000001592367572726-07776efd

The difference is just after the prefix shardId.
Normally the real shardId created by amazon use is composed by shardId prefix, 20-digit timestamp and 0-36 or more characters separated by '-'

The current shardId format is not valid for flink applications and it's not following the real pattern used by amazon

## Expected behavior

ShardId must follow the pattern
shardId prefix, 20-digit timestamp and 0-36 or more characters separated by '-'

## Actual behavior

The shardId follows the pattern
shardId prefix, 12 0s and 33 characters separated by '-'

# Steps to reproduce

Create a dynamodb table

## Command used to start LocalStack

I'm using docker and docker compose to run localstack


## Client code (AWS SDK code snippet, or sequence of "awslocal" commands)

aws --endpoint-url=http://localhost:4566 dynamodb create-table \
    --table-name temp4 \
    --attribute-definitions AttributeName=partition_key,AttributeType=S AttributeName=sort_key,AttributeType=S \
    --key-schema AttributeName=partition_key,KeyType=HASH AttributeName=sort_key,KeyType=RANGE \
    --provisioned-throughput ReadCapacityUnits=100,WriteCapacityUnits=100 \
    --stream-specification StreamEnabled=true,StreamViewType=NEW_AND_OLD_IMAGES


batch_size = check_batch_size_range(source_arn, batch_size)
    mapping = {
        'UUID': str(uuid.uuid4()),
        'StateTransitionReason': 'User action',
        'LastModified': float(time.mktime(datetime.utcnow().timetuple())),
        'BatchSize': batch_size,
        'State': 'Enabled' if enabled in [True, None] else 'Disabled',
        'FunctionArn': func_arn(function_name),
        'EventSourceArn': source_arn,
        'LastProcessingResult': 'OK',
        'StartingPosition': LAMBDA_DEFAULT_STARTING_POSITION
    }
    event_source_mappings.append(mapping)
    return mapping
def update_event_source(uuid_value, function_name, enabled, batch_size):
    for m in event_source_mappings:
        if uuid_value == m['UUID']:
            if function_name:
                m['FunctionArn'] = func_arn(function_name)
            batch_size = check_batch_size_range(m['EventSourceArn'], batch_size or m['BatchSize'])
            m['BatchSize'] = batch_size
            m['State'] = 'Enabled' if enabled is True else 'Disabled'
            m['LastModified'] = float(time.mktime(datetime.utcnow().timetuple()))
            return m
    return {}
def delete_event_source(uuid_value):