Elasticsearch Development

Archivematica 0.9+ stores AIP file information, such as METS data, using Elasticsearch. This data can be searched from the Archival Storage area of the dashboard or can be interfaced with programmatically.

To access indexed AIP data using a custom script or application, find an Elasticsearch interface library for the programming language you've chosen to use. In Archivematica we use Python with the pyes (https://github.com/aparo/pyes/) library. In our developer documentation, we'll outline the use of pyes to access AIP data, but any programming language/interface library, such as PHP and Elastica (https://github.com/ruflin/Elastica/), should work.

Requiring pyes and connecting to Elasticsearch

On this page we'll run through an example of interfacing with Elasticsearch data using a Python script that leverages the pyes library.

The first step, when using pyes, is to require the module. The following code imports pyes functionality on a system on which Archivematica is installed.

import sys
sys.path.append("/home/demo/archivematica/src/archivematicaCommon/lib/externals")
from pyes import *

Next you'll want to create a connection to Elasticsearch.

conn = ES('127.0.0.1:9200')

Querying Elasticsearch using pyes

You can now query Elasticsearch. Below is the code needed to do a "wildcard" search for all AIP files indexed by Elasticsearch and retrieve the first 20 items. Instead of doing a "wildcard" search you could also supply keywords, such as a certain AIP UUID.

start_page     = 1
items_per_page = 20

q = StringQuery('*')

try:
    results = conn.search_raw(
        query=q,
        indices='aips',
        type='aip',
        start=start_page - 1,
        size=items_per_page
     )
except:
    print 'Query error.'

Displaying pyes search results

Now that you've performed a search, you can display some results. The below logic cycles through each hit in the results, representing an AIP file, and prints the UUID of the AIP the file belongs in, the Elasticsearch document ID corresponding to the indexed file data, and the path of the file within the AIP.

if results:
    document_ids = []
    for item in results.hits.hits:
        aip = item._source
        print 'AIP ID: ' + aip['AIPUUID'] + ' / Document ID: ' + item._id
        print 'Filepath: ' + aip['filePath']
        print
        document_ids.append(item._id)

Fetching specific Elasticsearch documents

If you want to get Elasticsearch data for a specific file, you can use the Elasticsearch document ID. The above code populates the document_ids array and the below code uses this data, retrieving individual documents and extracting a specific item of data from each document.

for document_id in document_ids:
    data = conn.get(index_name, type_name, document_id)

    format = data['METS']['amdSec']['ns0:amdSec_list'][0]['ns0:techMD_list'][0]['ns0:mdWrap_list'][0]['ns0:xmlData_list'][0]['ns1:object_list'][0]['ns1:objectCharacteristics_list'][0]['ns1:format_list'][0]['ns1:formatDesignation_list'][0]['ns1:formatName']

    print 'Format for document ID ' + document_id + ' is ' + format