Ensure you have the necessary permissions and access credentials to read from your Elasticsearch cluster. You'll need the endpoint URL, any authentication credentials (such as an API key or username/password), and the index name containing the data you want to migrate.

Set up your development environment with the necessary libraries for interacting with Elasticsearch and AWS services. You'll need Python installed along with the `elasticsearch` and `boto3` libraries. You can install these using pip:
```bash
pip install elasticsearch boto3
```

Write a Python script to connect to your Elasticsearch instance and fetch the data. Use the `elasticsearch` library to scroll through the documents in your index. The scroll API is useful for extracting large datasets without hitting memory limits.
```python
from elasticsearch import Elasticsearch

es = Elasticsearch(['http://localhost:9200']) # Replace with your Elasticsearch endpoint
index_name = 'your-index'
result = es.search(index=index_name, scroll='2m', size=1000, body={"query": {"match_all": {}}})

sid = result['_scroll_id']
scroll_size = len(result['hits']['hits'])

while scroll_size > 0:
# Process each document here
for doc in result['hits']['hits']:
print(doc['_source']) # or store them in a list for batch processing

result = es.scroll(scroll_id=sid, scroll='2m')
sid = result['_scroll_id']
scroll_size = len(result['hits']['hits'])
```

Set up AWS credentials and configure your environment to interact with DynamoDB. Install the AWS CLI and configure it with your AWS access key, secret key, and region. This can be done by running:
```bash
aws configure
```

Before you can migrate data, ensure your DynamoDB table is set up correctly. Define the table schema, including the primary key attributes. You can create a table using the AWS Management Console, AWS CLI, or using a Python script with `boto3`.
```python
import boto3

dynamodb = boto3.resource('dynamodb', region_name='your-region')
table = dynamodb.create_table(
TableName='your-table-name',
KeySchema=[{'AttributeName': 'your_primary_key', 'KeyType': 'HASH'}],
AttributeDefinitions=[{'AttributeName': 'your_primary_key', 'AttributeType': 'S'}],
ProvisionedThroughput={'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5}
)
table.wait_until_exists()
```

Convert the extracted Elasticsearch documents into a format compatible with DynamoDB. This typically involves creating a dictionary with keys corresponding to the attribute names in your DynamoDB table and ensuring data types are compatible.

Use the `boto3` library to batch write data into DynamoDB. Since DynamoDB has write capacity limits, consider using the `batch_write_item` method, which allows up to 25 items per batch.
```python
table = dynamodb.Table('your-table-name')

with table.batch_writer() as batch:
for doc in your_document_list:
item = {
'your_primary_key': doc['your_primary_key_field'],
# Add other fields as necessary
}
batch.put_item(Item=item)
```

By following these steps, you can effectively migrate data from Elasticsearch to DynamoDB without relying on third-party tools.