An example of doing a "Top 10" query in elasticsearch using a term_stats facet.

top_books.py

import datetime
import random
from collections import defaultdict

from elasticsearch import Elasticsearch


INDEX = 'test-top-books'
TYPE = 'book-sales'
today = datetime.date.today()
books = defaultdict(int)


es = Elasticsearch()


if es.indices.exists(INDEX):
    es.indices.delete(INDEX)


# Create index.
es.indices.create(INDEX, {
    'settings': {
        'index': {
            'number_of_replicas': 0
        }
    }
})


# Populate some test data.
for i in range(1, 31):  # 30 days back
    for j in range(1, 11):  # 10 books
        sales = random.randint(1, 100)
        books[j] += sales
        body = {
            'book_id': j,
            'date': today - datetime.timedelta(days=i),
            'sales': sales,
        }
        es.index(INDEX, TYPE, body=body)


print 'Top 10 books:'
for id in sorted(books, key=lambda i: books[i], reverse=True):
    print 'Book ID:%d, Sales:%d' % (id, books[id])


# Refresh index.
es.indices.refresh(INDEX)


# Perform facet search.
res = es.search(INDEX, body={
    'query' : {
        'match_all': {}
    },
    'facets': {
        'top_books': {
            'terms_stats': {
                'key_field': 'book_id',
                'value_field': 'sales',
                'order': 'total'
            }
        }
    },
    'size': 0
})


print
print 'Top 10 according to Elasticsearch:'
for obj in res['facets']['top_books']['terms']:
    print 'Book ID:%d, Sales:%d' % (obj['term'], obj['total'])