Basic Index Example

This sample stores a document to an Elasticsearch server via the Elasticsearch Index API. The sample then retrieves the contents of the stored document via a call to the Elasticsearch Get API. The sample displays the results of the Index and Get calls.

For more information on the Elasticsearch Index API, see the Elasticsearch Python Index API and Elasticsearch REST Index API documentation.

Prerequisites

• The samples configuration step has been completed (see Samples Configuration).
• The Elasticsearch API DXL service is running, using the sample configuration (see Running).

Running

To run this sample execute the sample/basic/basic_index_example.py script as follows:

python sample/basic/basic_index_example.py

The output should appear similar to the following:

Response to the index request:
{
    "_id": "12345",
    "_index": "opendxl-elasticsearch-service-examples",
    "_shards": {
        "failed": 0,
        "successful": 2,
        "total": 2
    },
    "_type": "basic-example-doc",
    "_version": 1,
    "created": true,
    "result": "created"
}
Response to the get request:
{
    "_id": "12345",
    "_index": "opendxl-elasticsearch-service-examples",
    "_source": {
        "message": "Hello from OpenDXL",
        "source": "Basic Index Example"
    },
    "_type": "basic-example-doc",
    "_version": 1,
    "found": true
}

Details

In order to enable the use of the index and get APIs, both API names are listed in the apiNames setting under the [General] section in the sample "dxlelasticsearchservice.config" file that the service uses:

[General]
apiNames=index,get...

For more information on the configuration, see the Service Configuration File section.

The majority of the sample code is shown below:

# Create the client
with DxlClient(config) as client:

    # Connect to the fabric
    client.connect()

    logger.info("Connected to DXL fabric.")

    # Create the index request
    request_topic = "/opendxl-elasticsearch/service/elasticsearch-api/index"
    index_request = Request(request_topic)

    # Set the payload for the index request
    MessageUtils.dict_to_json_payload(index_request, {
        "index": DOCUMENT_INDEX,
        "doc_type": DOCUMENT_TYPE,
        "id": DOCUMENT_ID,
        "body": {
            "message": "Hello from OpenDXL",
            "source": "Basic Index Example"}})

    # Send the index request
    index_response = client.sync_request(index_request, timeout=30)

    if index_response.message_type != Message.MESSAGE_TYPE_ERROR:
        # Display results for the index request
        index_response_dict = MessageUtils.json_payload_to_dict(index_response)
        print("Response to the index request:\n{}".format(
            MessageUtils.dict_to_json(index_response_dict, pretty_print=True)))
    else:
        print("Error invoking service with topic '{}': {} ({})".format(
            request_topic, index_response.error_message,
            index_response.error_code))
        exit(1)

    # Create the get request
    request_topic = "/opendxl-elasticsearch/service/elasticsearch-api/get"
    get_request = Request(request_topic)

    # Set the payload for the get request
    MessageUtils.dict_to_json_payload(get_request, {
        "index": DOCUMENT_INDEX,
        "doc_type": DOCUMENT_TYPE,
        "id": DOCUMENT_ID})

    # Send the get request
    get_response = client.sync_request(get_request, timeout=30)

    if get_response.message_type != Message.MESSAGE_TYPE_ERROR:
        # Display results for the get request
        get_response_dict = MessageUtils.json_payload_to_dict(get_response)
        print("Response to the get request:\n{}".format(
            MessageUtils.dict_to_json(get_response_dict, pretty_print=True)))
    else:
        print("Error invoking service with topic '{}': {} ({})".format(
            request_topic, get_response.error_message,
            get_response.error_code))

After connecting to the DXL fabric, a request message is created with a topic that targets the "index" method of the Elasticsearch API DXL service.

The next step is to set the payload of the request message. The contents of the payload include the index, type (doc_type), and id at which to store the document. The contents also include a dict representing the body of the document to store.

From the Elasticsearch Python Index API documentation:

"Adds or updates a typed JSON document in a specific index, making it searchable."

The next step is to perform a synchronous request via the DXL fabric. If the response message is not an error, its contents are displayed.

To confirm that the document was stored properly, a second request message is created with a topic that targets the "get" method of the Elasticsearch API DXL service.

The next step is to set the payload of the request message. The contents of the payload include the index, type (doc_type), and id of the document to retrieve.

From the Elasticsearch Python Get API documentation:

"Get a typed JSON document from the index based on its id."

The next step is to perform a synchronous request via the DXL fabric. If the response message is not an error, its contents are displayed.